├── .gitignore ├── LICENSE ├── README.md ├── build.xml ├── lib ├── commons-io-2.5.jar ├── ij.jar ├── jfoenix.jar ├── logback-classic-1.1.7.jar ├── logback-core-1.1.7.jar ├── metadata-extractor-2.9.1.jar ├── neuroph-core-2.92.jar ├── neuroph-imgrec-2.92.jar ├── slf4j-api-1.7.21.jar └── xmpcore-5.1.2.jar ├── manifest.mf ├── nbproject ├── UPDATED.TXT ├── build-impl.xml ├── configs │ ├── Run_as_WebStart.properties │ └── Run_in_Browser.properties ├── genfiles.properties ├── jfx-impl.xml ├── jfx-impl_backup.xml ├── jfx-impl_backup_1.xml ├── jfx-impl_backup_2.xml ├── jfx-impl_backup_3.xml ├── jfx-impl_backup_4.xml ├── jfx-impl_backup_5.xml ├── jfx-impl_backup_6.xml ├── project.properties └── project.xml ├── nnet ├── CNN2.nnet ├── CNN_V1.0.nnet ├── CNN_V2.0.nnet ├── CNN_V3.0.nnet └── MLPV2.0.nnet └── src ├── com └── gc │ └── fakeimagedetection │ ├── core │ ├── FIDNetworkAnalyser.java │ ├── FIDNetworkTrainer.java │ ├── FIDPreprocessor.java │ ├── constants │ │ └── ConstantObjects.java │ ├── errorlevelanalysis │ │ ├── ErrorLevelAnalyzer.java │ │ ├── FIDErrorLevelAnalysis.java │ │ └── ImageStandardizer.java │ ├── listener │ │ ├── BatchImageTestingListener.java │ │ ├── BatchImageTrainingListener.java │ │ ├── ErrorLevelAnalysisListener.java │ │ ├── ErrorLevelAnalysisUpdateListener.java │ │ ├── NeuralNetworkCreationCompleteListener.java │ │ ├── NeuralnetProcessorListener.java │ │ └── ThreadCompleteListener.java │ ├── metadata │ │ └── MetadataProcessor.java │ ├── multithread │ │ └── NotifyingThread.java │ ├── neuralnet │ │ └── MLPNetworkMaker.java │ ├── processor │ │ └── NeuralNetProcessor.java │ ├── tester │ │ └── BatchImageTestProcessor.java │ └── trainer │ │ ├── BatchImageTrainer.java │ │ └── SingleImageTrainer.java │ └── ui │ ├── BatchImageTester.java │ ├── ELABatchImageProcessor.java │ ├── Main.java │ ├── NeuralNetCreator.java │ ├── SingleImageCheck.java │ ├── TrainerMain.java │ ├── alert │ ├── Calert.java │ └── CommonUtil.java │ └── controllers │ ├── BatchImageProcessorController.java │ ├── BatchImageTesterController.java │ ├── LaunchScreeenController.java │ ├── MetadataDisplayController.java │ ├── MetadataResultController.java │ ├── NetworkcreatorController.java │ ├── NeuralnetInterfaceController.java │ ├── SingleImageAnalyzerController.java │ └── TrainingInterfaceController.java └── resources ├── fxml ├── batchimageprocessor.fxml ├── batchimagetester.fxml ├── home.png ├── infinity.png ├── launch.fxml ├── metadatadisplay.fxml ├── metadataresult.fxml ├── networkcreator.fxml ├── neuralinterface.fxml ├── singleimage.fxml └── traininginterface.fxml ├── icon ├── icon.png └── icon_high.png └── stylesheets └── main.css /.gitignore: -------------------------------------------------------------------------------- 1 | /nbproject/private/ 2 | /dist/ 3 | /build/ 4 | /output/ 5 | /tmp/ -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Fake Image Detection Using Machine Learning 2 | 3 | The objective of this project is to identify fake images(Fake images are the images that are digitally altered images). The problem with existing fake image detection system is that they can be used detect only specific tampering methods like splicing, coloring etc. We approached the problem using machine learning and neural network to detect almost all kinds of tampering on images. 4 | 5 | Using latest image editing softwares, it is possible to make alterations on image which are too difficult for human eye to detect. Even with a complex neural network, it is not possible to determine whether an image is fake or not without identifying a common factor across almost all fake images. So, instead of giving direct raw pixels to the neural network, we gave error level analysed image. 6 | 7 | This project provides two level analysis for the image. At first level, it checks the image metadata. Image metadata is not that much reliable since it can be altered using simple programs. But most of the images we come across will have non-altered metadata which helps to identify the alterations. For example, if an image is edited with Adobe Photoshop, the metadata will contain even the version of the Adobe Photoshop used. 8 | 9 | In the second level, the image is converted into error level analysed format and will be resized to 100px x 100px image. Then these 10,000 pixels with RGB values (30,000 inputs) is given in to the input layer of Multilayer perceptron network. Output layer contain two neurons. One for fake image and one for real image. Depending upon the value of these neuron outputs along with metadata analyser output, we determine whether the image is fake or not and how much chance is there for the given image to be tampered. 10 | 11 | ### Feature Engineering 12 | 1. Dr. Neal Krawetz proposed a method called [Error Level Analysis(ELA)](http://www.hackerfactor.com/papers/bh-usa-07-krawetz-wp.pdf) that exploits the lossy compression of JPEG images. When an image is altered, the compression ratio of the specific portion changes with respect to other parts. A well trained neural network can detect the anomaly by and determine whether the image is fake or not. 13 | 2. The second parameter considered is metadata of the image. A parallel module is added to the program which checks the metadata to determine the signature of various image editing programs. Since it is costly to execute a neural network, the metadata inspection will considerably increase the performance by detecting tampering at an early stage. 14 | 15 | ### Neural network structure 16 | | Layer | Neurons | 17 | | ------------- | ------------- | 18 | | Input Layer | 30,000 | 19 | | Hidden Layer 1 | 5000 - Sigmoid | 20 | | Hidden Layer 2 | 1000 - Sigmoid | 21 | | Hidden Layer 3 | 100 - Sigmoid | 22 | | Output Layer | 2 | 23 | 24 | 25 | ### Watch on YouTube 26 | [![Watch a video](https://img.youtube.com/vi/MVIN9HrS8UY/0.jpg)](https://www.youtube.com/watch?v=MVIN9HrS8UY) 27 | 28 | ### Tools Used 29 | 30 | #### [Neuroph Studio](http://neuroph.sourceforge.net/) 31 | Neuroph studio is an open source Java neural network framework that helps to easily build and use neural networks. It also provides a direct interface for loading images 32 | #### [Metadata-extractor](https://github.com/drewnoakes/metadata-extractor) 33 | Metadata-extractor is an open source java library used to extract metadata from images. 34 | #### [JavaFX](http://docs.oracle.com/javase/8/javase-clienttechnologies.htm) 35 | JavaFX is used to implement modern user interface for the application. 36 | 37 | ### Flow Chart : Detection 38 | 39 | 40 | ### Flow Chart : Training 41 | 42 | 43 | ### Project Status 44 | - [x] Implement Metadata Procesing Module 45 | - [x] Design a User Interface 46 | - [x] Implement Image Feature Extractor 47 | - [x] Design Neural Network using Neuroph Studio 48 | - [x] Implement Neural Network interface with JavaFX 49 | - [x] Connect Neural Network 50 | - [x] Integrate Neural Network to Master 51 | - [x] Train Network 52 | - [x] Test Network 53 | - [x] Read feedback from user and learn instantly 54 | - [x] Add network training interface 55 | - [x] Add module to apply error level analysis on a set of images 56 | - [x] Improve look and feel 57 | - [x] Train with more data 58 | - [x] Add batch testing module 59 | - [x] Detach User Inteface from core 60 | - [x] Implement Command Line Interface 61 | - [ ] Reach success rate of 90% 62 | 63 | Journal link : https://www.academia.edu/37977449/Fake_Image_Detection_Using_Machine_Learning 64 | 65 | 66 | ### Screenshots 67 | 68 | 69 | 70 | 71 | 72 | 73 | -------------------------------------------------------------------------------- /build.xml: -------------------------------------------------------------------------------- 1 | 2 | Builds, tests, and runs the project Fake Image Detection. 3 | 4 | 53 | 54 | -------------------------------------------------------------------------------- /lib/commons-io-2.5.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/commons-io-2.5.jar -------------------------------------------------------------------------------- /lib/ij.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/ij.jar -------------------------------------------------------------------------------- /lib/jfoenix.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/jfoenix.jar -------------------------------------------------------------------------------- /lib/logback-classic-1.1.7.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/logback-classic-1.1.7.jar -------------------------------------------------------------------------------- /lib/logback-core-1.1.7.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/logback-core-1.1.7.jar -------------------------------------------------------------------------------- /lib/metadata-extractor-2.9.1.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/metadata-extractor-2.9.1.jar -------------------------------------------------------------------------------- /lib/neuroph-core-2.92.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/neuroph-core-2.92.jar -------------------------------------------------------------------------------- /lib/neuroph-imgrec-2.92.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/neuroph-imgrec-2.92.jar -------------------------------------------------------------------------------- /lib/slf4j-api-1.7.21.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/slf4j-api-1.7.21.jar -------------------------------------------------------------------------------- /lib/xmpcore-5.1.2.jar: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/lib/xmpcore-5.1.2.jar -------------------------------------------------------------------------------- /manifest.mf: -------------------------------------------------------------------------------- 1 | Manifest-Version: 1.0 2 | X-COMMENT: Main-Class will be added automatically by build 3 | 4 | -------------------------------------------------------------------------------- /nbproject/UPDATED.TXT: -------------------------------------------------------------------------------- 1 | ================================================= 2 | Project Fake Image Detection build script updated 3 | ================================================= 4 | 5 | Project build script file jfx-impl.xml in nbproject sub-directory has not been recognized 6 | as compliant with this version of NetBeans JavaFX support module. To ensure correct 7 | and complete functionality within this NetBeans installation the script file has been 8 | backed up to jfx-impl_backup_6.xml and then updated to the currently supported state. 9 | 10 | FX Project build script auto-update may be triggered on project open either after 11 | NetBeans installation update or by manual changes in jfx-impl.xml. Please note that 12 | changing jfx-impl.xml manually is not recommended. Any build customization code should 13 | be placed only in build.xml in project root directory. 14 | 15 | Remark: The auto-update mechanism can be disabled by setting property 16 | javafx.disable.autoupdate=true 17 | Automatic opening of this notification when project files are updated can be disabled by setting property 18 | javafx.disable.autoupdate.notification=true 19 | (in build.properties, private.properties or project.properties). 20 | 21 | Remark: Files nbproject/jfx-impl_backup*.xml and this file nbproject/UPDATED.TXT 22 | are not used when building the project and can be freely deleted. 23 | 24 | -------------------------------------------------------------------------------- /nbproject/configs/Run_as_WebStart.properties: -------------------------------------------------------------------------------- 1 | # Do not modify this property in this configuration. It can be re-generated. 2 | $label=Run as WebStart 3 | -------------------------------------------------------------------------------- /nbproject/configs/Run_in_Browser.properties: -------------------------------------------------------------------------------- 1 | # Do not modify this property in this configuration. It can be re-generated. 2 | $label=Run in Browser 3 | -------------------------------------------------------------------------------- /nbproject/genfiles.properties: -------------------------------------------------------------------------------- 1 | build.xml.data.CRC32=6f51bc78 2 | build.xml.script.CRC32=91121d0f 3 | build.xml.stylesheet.CRC32=8064a381@1.79.1.48 4 | # This file is used by a NetBeans-based IDE to track changes in generated files such as build-impl.xml. 5 | # Do not edit this file. You may delete it but then the IDE will never regenerate such files for you. 6 | nbproject/build-impl.xml.data.CRC32=6f51bc78 7 | nbproject/build-impl.xml.script.CRC32=0feb16f7 8 | nbproject/build-impl.xml.stylesheet.CRC32=05530350@1.79.1.48 9 | -------------------------------------------------------------------------------- /nbproject/project.properties: -------------------------------------------------------------------------------- 1 | annotation.processing.enabled=true 2 | annotation.processing.enabled.in.editor=false 3 | annotation.processing.processors.list= 4 | annotation.processing.run.all.processors=true 5 | annotation.processing.source.output=${build.generated.sources.dir}/ap-source-output 6 | application.title=Fake Image Detection 7 | application.vendor=afsal 8 | build.classes.dir=${build.dir}/classes 9 | build.classes.excludes=**/*.java,**/*.form 10 | # This directory is removed when the project is cleaned: 11 | build.dir=build 12 | build.generated.dir=${build.dir}/generated 13 | build.generated.sources.dir=${build.dir}/generated-sources 14 | # Only compile against the classpath explicitly listed here: 15 | build.sysclasspath=ignore 16 | build.test.classes.dir=${build.dir}/test/classes 17 | build.test.results.dir=${build.dir}/test/results 18 | compile.on.save=true 19 | compile.on.save.unsupported.javafx=true 20 | # Uncomment to specify the preferred debugger connection transport: 21 | #debug.transport=dt_socket 22 | debug.classpath=\ 23 | ${run.classpath} 24 | debug.test.classpath=\ 25 | ${run.test.classpath} 26 | # This directory is removed when the project is cleaned: 27 | dist.dir=dist 28 | dist.jar=${dist.dir}/Fake Image Detection.jar 29 | dist.javadoc.dir=${dist.dir}/javadoc 30 | endorsed.classpath= 31 | excludes= 32 | file.reference.commons-io-2.5.jar=lib/commons-io-2.5.jar 33 | file.reference.ij.jar=lib/ij.jar 34 | file.reference.jfoenix.jar=lib/jfoenix.jar 35 | file.reference.logback-classic-1.1.7.jar=lib/logback-classic-1.1.7.jar 36 | file.reference.logback-core-1.1.7.jar=lib/logback-core-1.1.7.jar 37 | file.reference.metadata-extractor-2.9.1.jar=lib/metadata-extractor-2.9.1.jar 38 | file.reference.neuroph-core-2.92.jar=lib/neuroph-core-2.92.jar 39 | file.reference.neuroph-imgrec-2.92.jar=lib/neuroph-imgrec-2.92.jar 40 | file.reference.slf4j-api-1.7.21.jar=lib/slf4j-api-1.7.21.jar 41 | file.reference.xmpcore-5.1.2.jar=lib/xmpcore-5.1.2.jar 42 | includes=** 43 | # Non-JavaFX jar file creation is deactivated in JavaFX 2.0+ projects 44 | jar.archive.disabled=true 45 | jar.compress=false 46 | javac.classpath=\ 47 | ${javafx.classpath.extension}:\ 48 | ${file.reference.jfoenix.jar}:\ 49 | ${file.reference.metadata-extractor-2.9.1.jar}:\ 50 | ${file.reference.xmpcore-5.1.2.jar}:\ 51 | ${file.reference.ij.jar}:\ 52 | ${file.reference.neuroph-core-2.92.jar}:\ 53 | ${file.reference.neuroph-imgrec-2.92.jar}:\ 54 | ${file.reference.slf4j-api-1.7.21.jar}:\ 55 | ${file.reference.logback-classic-1.1.7.jar}:\ 56 | ${file.reference.logback-core-1.1.7.jar}:\ 57 | ${file.reference.commons-io-2.5.jar} 58 | # Space-separated list of extra javac options 59 | javac.compilerargs= 60 | javac.deprecation=false 61 | javac.external.vm=false 62 | javac.processorpath=\ 63 | ${javac.classpath} 64 | javac.source=1.8 65 | javac.target=1.8 66 | javac.test.classpath=\ 67 | ${javac.classpath}:\ 68 | ${build.classes.dir} 69 | javac.test.processorpath=\ 70 | ${javac.test.classpath} 71 | javadoc.additionalparam= 72 | javadoc.author=false 73 | javadoc.encoding=${source.encoding} 74 | javadoc.noindex=false 75 | javadoc.nonavbar=false 76 | javadoc.notree=false 77 | javadoc.private=false 78 | javadoc.splitindex=true 79 | javadoc.use=true 80 | javadoc.version=false 81 | javadoc.windowtitle= 82 | javafx.application.implementation.version=1.0 83 | javafx.binarycss=false 84 | javafx.classpath.extension=\ 85 | ${java.home}/lib/javaws.jar:\ 86 | ${java.home}/lib/deploy.jar:\ 87 | ${java.home}/lib/plugin.jar 88 | javafx.deploy.adddesktopshortcut=false 89 | javafx.deploy.addstartmenushortcut=false 90 | javafx.deploy.allowoffline=true 91 | # If true, application update mode is set to 'background', if false, update mode is set to 'eager' 92 | javafx.deploy.backgroundupdate=false 93 | javafx.deploy.disable.proxy=false 94 | javafx.deploy.embedJNLP=true 95 | javafx.deploy.includeDT=true 96 | javafx.deploy.installpermanently=false 97 | javafx.deploy.permissionselevated=false 98 | # Set true to prevent creation of temporary copy of deployment artifacts before each run (disables concurrent runs) 99 | javafx.disable.concurrent.runs=false 100 | # Set true to enable multiple concurrent runs of the same WebStart or Run-in-Browser project 101 | javafx.enable.concurrent.external.runs=false 102 | # This is a JavaFX project 103 | javafx.enabled=true 104 | javafx.fallback.class=com.javafx.main.NoJavaFXFallback 105 | # Main class for JavaFX 106 | javafx.main.class=com.gc.fakeimagedetection.ui.Main 107 | javafx.preloader.class= 108 | # This project does not use Preloader 109 | javafx.preloader.enabled=false 110 | javafx.preloader.jar.filename= 111 | javafx.preloader.jar.path= 112 | javafx.preloader.project.path= 113 | javafx.preloader.type=none 114 | # Set true for GlassFish only. Rebases manifest classpaths of JARs in lib dir. Not usable with signed JARs. 115 | javafx.rebase.libs=false 116 | javafx.run.height=600 117 | javafx.run.width=800 118 | javafx.signing.blob=false 119 | javafx.signing.enabled=false 120 | javafx.signing.type=notsigned 121 | # Pre-JavaFX 2.0 WebStart is deactivated in JavaFX 2.0+ projects 122 | jnlp.enabled=false 123 | # Main class for Java launcher 124 | main.class=com.javafx.main.Main 125 | # For improved security specify narrower Codebase manifest attribute to prevent RIAs from being repurposed 126 | manifest.custom.codebase=* 127 | # Specify Permissions manifest attribute to override default (choices: sandbox, all-permissions) 128 | manifest.custom.permissions= 129 | manifest.file=manifest.mf 130 | meta.inf.dir=${src.dir}/META-INF 131 | mkdist.disabled=false 132 | native.bundling.enabled=false 133 | platform.active=default_platform 134 | run.classpath=\ 135 | ${dist.jar}:\ 136 | ${javac.classpath}:\ 137 | ${build.classes.dir} 138 | run.jvmargs=-Xmx64m -Xmx6096m 139 | run.test.classpath=\ 140 | ${javac.test.classpath}:\ 141 | ${build.test.classes.dir} 142 | source.encoding=UTF-8 143 | src.dir=src 144 | test.src.dir=test 145 | -------------------------------------------------------------------------------- /nbproject/project.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | org.netbeans.modules.java.j2seproject 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | Fake Image Detection 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | -------------------------------------------------------------------------------- /nnet/CNN2.nnet: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/nnet/CNN2.nnet -------------------------------------------------------------------------------- /nnet/CNN_V1.0.nnet: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/nnet/CNN_V1.0.nnet -------------------------------------------------------------------------------- /nnet/CNN_V2.0.nnet: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/nnet/CNN_V2.0.nnet -------------------------------------------------------------------------------- /nnet/CNN_V3.0.nnet: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/nnet/CNN_V3.0.nnet -------------------------------------------------------------------------------- /nnet/MLPV2.0.nnet: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/nnet/MLPV2.0.nnet -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/FIDNetworkAnalyser.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core; 2 | 3 | import com.gc.fakeimagedetection.core.errorlevelanalysis.FIDErrorLevelAnalysis; 4 | import com.gc.fakeimagedetection.core.listener.ErrorLevelAnalysisListener; 5 | import java.awt.Dimension; 6 | import java.awt.image.BufferedImage; 7 | import java.io.FileInputStream; 8 | import java.io.FileNotFoundException; 9 | import java.util.HashMap; 10 | import org.neuroph.core.NeuralNetwork; 11 | import org.neuroph.imgrec.ImageRecognitionPlugin; 12 | 13 | public class FIDNetworkAnalyser implements ErrorLevelAnalysisListener { 14 | 15 | private NeuralNetwork nnet; 16 | 17 | public FIDNetworkAnalyser(String nSourceFile) throws FileNotFoundException { 18 | nnet = NeuralNetwork.load(new FileInputStream(nSourceFile)); // load trained neural network saved with Neuroph Studio 19 | } 20 | 21 | public static void main(String[] args) throws FileNotFoundException { 22 | if (args == null || args.length < 5) { 23 | System.err.println("Usage : "); 24 | } 25 | String neuralSource = args[0]; 26 | String imageLoc = args[1]; 27 | String quality = args[2]; 28 | String sWidth = args[3]; 29 | String sHeight = args[4]; 30 | 31 | new FIDNetworkAnalyser(neuralSource) 32 | .run(imageLoc, Integer.parseInt(quality), 33 | new Dimension(Integer.parseInt(sWidth), Integer.parseInt(sHeight))); 34 | 35 | } 36 | 37 | private void run(String imageLocation, int quality, Dimension dim) { 38 | FIDErrorLevelAnalysis elaAnalyzer = new FIDErrorLevelAnalysis(imageLocation, quality, dim, this); 39 | elaAnalyzer.start(); 40 | } 41 | 42 | public void processOnNeuralNetwork(BufferedImage elaImage) { 43 | ImageRecognitionPlugin imageRecognition = (ImageRecognitionPlugin) nnet.getPlugin(ImageRecognitionPlugin.class); // get the image recognition plugin from neural network 44 | HashMap output = imageRecognition.recognizeImage(elaImage); 45 | if (output == null) { 46 | System.err.println("Image Recognition Failed"); 47 | } 48 | System.out.println(output.toString()); 49 | } 50 | 51 | @Override 52 | public void elaCompleted(BufferedImage image) { 53 | if(image==null) 54 | return; 55 | processOnNeuralNetwork(image); 56 | } 57 | } 58 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/FIDNetworkTrainer.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core; 2 | 3 | import com.gc.fakeimagedetection.core.listener.BatchImageTrainingListener; 4 | import com.gc.fakeimagedetection.core.trainer.BatchImageTrainer; 5 | import java.awt.Dimension; 6 | import java.io.File; 7 | import java.util.ArrayList; 8 | import java.util.Arrays; 9 | 10 | public class FIDNetworkTrainer implements BatchImageTrainingListener { 11 | 12 | private final float MERROR = 0.01f; 13 | private final float LEARNING_RATE = 0.1f; 14 | private final float MOMENTUM = 0.7f; 15 | 16 | public static void main(String[] args) { 17 | if (args == null || args.length < 5) { 18 | System.err.println("usage : "); 19 | return; 20 | } 21 | 22 | String sourceDir = args[0]; 23 | String neuralDir = args[1]; 24 | String sWidth = args[2]; 25 | String sHeight = args[3]; 26 | String imageLabelString = args[4]; 27 | 28 | new FIDNetworkTrainer().run(sourceDir, neuralDir, sWidth, sHeight, imageLabelString); 29 | } 30 | 31 | @Override 32 | public void batchImageTrainingCompleted() { 33 | System.out.println("Training Completed"); 34 | } 35 | 36 | @Override 37 | public void batchImageTrainingUpdate(int iteration, Double error) { 38 | System.out.println("Iteration " + iteration + "\t Error = " + error); 39 | } 40 | 41 | private void run(String sourceDir, String neuralDir, String sWidth, String sHeight, String imageLabelString) { 42 | ArrayList labels = new ArrayList<>(); 43 | labels.addAll(Arrays.asList(imageLabelString.split(","))); 44 | BatchImageTrainer neuralTrainer 45 | = new BatchImageTrainer(new File(sourceDir), new File(neuralDir), 46 | new Dimension(Integer.parseInt(sWidth), Integer.parseInt(sHeight)), labels, this); 47 | neuralTrainer.setMaxError(MERROR); 48 | neuralTrainer.setMomentum(MOMENTUM); 49 | neuralTrainer.setLearningRate(LEARNING_RATE); 50 | neuralTrainer.start(); 51 | } 52 | 53 | } 54 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/FIDPreprocessor.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core; 2 | 3 | import com.gc.fakeimagedetection.core.errorlevelanalysis.ImageStandardizer; 4 | import java.awt.Dimension; 5 | import java.io.File; 6 | 7 | public class FIDPreprocessor { 8 | 9 | public static void main(String[] args) { 10 | if (args == null || args.length < 5) { 11 | System.err.println("Usage : "); 12 | return; 13 | } 14 | String srcDir = args[0]; 15 | String destDir = args[1]; 16 | String sWidth = args[2]; 17 | String sHeight = args[3]; 18 | String outLabel = args[4]; 19 | 20 | ImageStandardizer preprocessor 21 | = new ImageStandardizer(new File(srcDir), new File(destDir), 22 | new Dimension(Integer.parseInt(sWidth), Integer.parseInt(sHeight)), outLabel); 23 | } 24 | } 25 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/constants/ConstantObjects.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.constants; 2 | 3 | public class ConstantObjects { 4 | 5 | public static String[] supportedExtensions 6 | = {"JPG", "jpg", "JPEG", "PNG", "png", "TIFF", "TIF", "tif"}; 7 | public static String neuralNetworkPath = "nnet/MLPV2.0.nnet"; 8 | public static Boolean shouldPropogateResult = true; 9 | public static float fakeness = -1; 10 | public static float realness = -1; 11 | } 12 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/errorlevelanalysis/ErrorLevelAnalyzer.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.errorlevelanalysis; 2 | 3 | import com.gc.fakeimagedetection.core.listener.ErrorLevelAnalysisUpdateListener; 4 | import com.gc.fakeimagedetection.ui.alert.Calert; 5 | import com.gc.fakeimagedetection.core.multithread.NotifyingThread; 6 | import ij.ImagePlus; 7 | import ij.io.FileSaver; 8 | import static ij.io.FileSaver.setJpegQuality; 9 | import ij.plugin.ContrastEnhancer; 10 | import ij.plugin.ImageCalculator; 11 | import ij.process.ImageProcessor; 12 | import java.awt.Dimension; 13 | import java.awt.Image; 14 | import java.awt.Rectangle; 15 | import java.io.File; 16 | import java.io.IOException; 17 | import java.text.DecimalFormat; 18 | import java.util.ArrayList; 19 | import javafx.scene.control.Alert; 20 | import javax.imageio.ImageIO; 21 | 22 | public class ErrorLevelAnalyzer extends NotifyingThread { 23 | 24 | String fileLocation; 25 | String destination = "output/processed"; 26 | int quality = 95; 27 | Boolean runningStatus = false; 28 | Dimension sampledDimension; 29 | String outLabel; 30 | ArrayList supportedExtensions; 31 | ErrorLevelAnalysisUpdateListener listener; 32 | int baseCount = 1; 33 | 34 | public ErrorLevelAnalyzer(String fileLocation, String destination, int quality) { 35 | this.fileLocation = fileLocation; 36 | this.destination = destination + "/"; 37 | this.quality = quality; 38 | } 39 | 40 | public void setListener(ErrorLevelAnalysisUpdateListener listener) { 41 | this.listener = listener; 42 | } 43 | 44 | public ErrorLevelAnalyzer(String dirLoc, String destination, int quality, ArrayList supportedExtensions, Dimension dimension, String outLabel) { 45 | this.fileLocation = dirLoc; 46 | this.quality = quality; 47 | this.sampledDimension = dimension; 48 | this.supportedExtensions = supportedExtensions; 49 | this.destination = destination + "/"; 50 | this.outLabel = outLabel; 51 | } 52 | 53 | public void setSampledDimension(Dimension sampledDimension) { 54 | this.sampledDimension = sampledDimension; 55 | } 56 | 57 | public Dimension getSampledDimension() { 58 | return sampledDimension; 59 | } 60 | 61 | @Override 62 | public void doRun() { 63 | try { 64 | System.out.println("Changing Images to size " + sampledDimension); 65 | 66 | File[] availableFiles = new File(fileLocation).listFiles(); 67 | float totalSize = availableFiles.length; 68 | float processedSize = 0; 69 | checkForImageConflict(); 70 | 71 | for (File file : availableFiles) { 72 | String ext = file.getName().split("[.]")[1]; 73 | if (!supportedExtensions.contains(ext)) { 74 | System.out.println("Dropping " + file.getName() + " due to unsupported extension --" + file.getName().split("[.]")[1]); 75 | continue; 76 | } 77 | runningStatus = true; 78 | Image img; 79 | try { 80 | img = ImageIO.read(file); 81 | } catch (IOException ex) { 82 | System.err.println("Null Image"); 83 | return; 84 | } 85 | ImagePlus orig = new ImagePlus("Source Image", img); 86 | if (orig.getWidth() < sampledDimension.getWidth() || orig.getHeight() < sampledDimension.getHeight()) { 87 | System.err.println("Too Small to process"); 88 | continue; 89 | } 90 | 91 | String basePath = "output/"; 92 | String origPath = basePath + "original.jpg"; 93 | String resavedPath = basePath + "resaved.jpg"; 94 | String elaPath = basePath + "ELA.png"; 95 | 96 | FileSaver fs = new FileSaver(orig); 97 | setJpegQuality(100); 98 | fs.saveAsJpeg(origPath); 99 | 100 | setJpegQuality(quality); 101 | fs.saveAsJpeg(resavedPath); 102 | ImagePlus resaved = new ImagePlus(resavedPath); 103 | 104 | ImageCalculator calc = new ImageCalculator(); 105 | ImagePlus diff; 106 | try { 107 | diff = calc.run("create difference", orig, resaved); 108 | } catch (Exception e) { 109 | Calert.showAlert("Error Occured", e.getMessage(), Alert.AlertType.ERROR); 110 | continue; 111 | } 112 | diff.setTitle("ELA @ " + quality + "%"); 113 | 114 | ContrastEnhancer c = new ContrastEnhancer(); 115 | c.stretchHistogram(diff, 0.05); 116 | 117 | ImageProcessor ip = diff.getProcessor(); 118 | ImageProcessor imp; 119 | if (ip.getWidth() > ip.getHeight()) { 120 | Rectangle rec = new Rectangle(0, 0, ip.getHeight(), ip.getHeight()); 121 | ip.setRoi(rec); 122 | imp = ip.crop(); 123 | } else { 124 | Rectangle rec = new Rectangle(0, 0, ip.getWidth(), ip.getWidth()); 125 | ip.setRoi(rec); 126 | imp = ip.crop(); 127 | } 128 | imp = imp.resize((int) sampledDimension.getWidth(), (int) sampledDimension.getHeight()); 129 | FileSaver resultSaver = new FileSaver(new ImagePlus("Result", imp.getBufferedImage())); 130 | 131 | DecimalFormat format = new DecimalFormat("#"); 132 | String savePath = destination + outLabel + format.format(baseCount + processedSize) + ".png"; 133 | resultSaver.saveAsPng(savePath); 134 | 135 | runningStatus = false; 136 | 137 | float percentage = processedSize / totalSize; 138 | 139 | String status = "Processing " + file.getName() + " " + format.format(processedSize) + " / " + format.format(totalSize); 140 | listener.iterationCompleted(status, percentage); 141 | processedSize++; 142 | 143 | } 144 | } catch (Exception e) { 145 | System.err.println("Error Occured at Ela_processor :" + e.getMessage()); 146 | } 147 | } 148 | 149 | private void checkForImageConflict() { 150 | baseCount = 1; 151 | while (true) { 152 | String savePath = destination + outLabel + (baseCount + 1) + ".png"; 153 | if (new File(savePath).exists()) { 154 | baseCount++; 155 | } else { 156 | break; 157 | } 158 | } 159 | System.out.println("There are " + (baseCount - 1) + " images already. Starting from " + baseCount); 160 | } 161 | 162 | } 163 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/errorlevelanalysis/FIDErrorLevelAnalysis.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.errorlevelanalysis; 2 | 3 | import com.gc.fakeimagedetection.core.listener.ErrorLevelAnalysisListener; 4 | import com.gc.fakeimagedetection.core.multithread.NotifyingThread; 5 | import com.gc.fakeimagedetection.ui.alert.Calert; 6 | import ij.ImagePlus; 7 | import ij.io.FileSaver; 8 | import static ij.io.FileSaver.setJpegQuality; 9 | import ij.plugin.ContrastEnhancer; 10 | import ij.plugin.ImageCalculator; 11 | import ij.process.ImageProcessor; 12 | import java.awt.Dimension; 13 | import java.awt.Image; 14 | import java.awt.Rectangle; 15 | import java.io.File; 16 | import java.io.IOException; 17 | import javafx.application.Platform; 18 | import javafx.scene.control.Alert; 19 | import javax.imageio.ImageIO; 20 | 21 | public class FIDErrorLevelAnalysis extends NotifyingThread { 22 | 23 | String fileLocation; 24 | int quality = 95; 25 | Boolean runningStatus = false; 26 | Dimension sampledDimension; 27 | ErrorLevelAnalysisListener listener; 28 | 29 | public FIDErrorLevelAnalysis(String fileLocation, 30 | int quality, Dimension sampledDimension, ErrorLevelAnalysisListener listener) { 31 | this.fileLocation = fileLocation; 32 | this.quality = quality; 33 | this.sampledDimension = sampledDimension; 34 | this.listener = listener; 35 | } 36 | 37 | @Override 38 | public void doRun() { 39 | try { 40 | Image img; 41 | try { 42 | System.out.println("Loading Image :" + fileLocation); 43 | img = ImageIO.read(new File(fileLocation)); 44 | } catch (IOException ex) { 45 | System.err.println("Null Image"); 46 | return; 47 | } 48 | System.out.println("Dimension is set to " + sampledDimension); 49 | ImagePlus orig = new ImagePlus("Source Image", img); 50 | 51 | String basePath = "tmp/"; 52 | File file = new File(basePath); 53 | if (!file.exists()) { 54 | file.mkdir(); 55 | } 56 | String origPath = basePath + "-original.jpg"; 57 | String resavedPath = basePath + "-resaved.jpg"; 58 | String elaPath = basePath + "-ELA.png"; 59 | 60 | FileSaver fs = new FileSaver(orig); 61 | setJpegQuality(100); 62 | fs.saveAsJpeg(origPath); 63 | 64 | setJpegQuality(quality); 65 | fs.saveAsJpeg(resavedPath); 66 | ImagePlus resaved = new ImagePlus(resavedPath); 67 | 68 | ImageCalculator calc = new ImageCalculator(); 69 | ImagePlus diff = calc.run("create difference", orig, resaved); 70 | diff.setTitle("ELA @ " + quality + "%"); 71 | 72 | ContrastEnhancer c = new ContrastEnhancer(); 73 | c.stretchHistogram(diff, 0.05); 74 | ImageProcessor ip = diff.getProcessor(); 75 | 76 | ImageProcessor imp; 77 | if (ip.getWidth() > ip.getHeight()) { 78 | Rectangle rec = new Rectangle(0, 0, ip.getHeight(), ip.getHeight()); 79 | ip.setRoi(rec); 80 | imp = ip.crop(); 81 | } else { 82 | Rectangle rec = new Rectangle(0, 0, ip.getWidth(), ip.getWidth()); 83 | ip.setRoi(rec); 84 | imp = ip.crop(); 85 | } 86 | 87 | imp = imp.resize((int) sampledDimension.getWidth(), (int) sampledDimension.getHeight()); 88 | listener.elaCompleted(imp.getBufferedImage()); 89 | } catch (Exception e) { 90 | //JavaFX UI thread is different from current Thread 91 | System.err.println(e.toString()); 92 | Platform.runLater(new Runnable() { 93 | @Override 94 | public void run() { 95 | Calert.showAlert("Fatal Error Occured", "Neural Network Error", Alert.AlertType.ERROR); 96 | } 97 | }); 98 | listener.elaCompleted(null); 99 | } 100 | } 101 | 102 | } 103 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/errorlevelanalysis/ImageStandardizer.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.errorlevelanalysis; 2 | 3 | import com.gc.fakeimagedetection.core.listener.ErrorLevelAnalysisUpdateListener; 4 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 5 | import com.gc.fakeimagedetection.core.listener.ThreadCompleteListener; 6 | import java.awt.Dimension; 7 | import java.io.File; 8 | import java.util.ArrayList; 9 | import java.util.Arrays; 10 | 11 | public final class ImageStandardizer implements ThreadCompleteListener { 12 | 13 | File sourceDir = null; 14 | File destDir = null; 15 | Dimension resolution = null; 16 | File[] availableFiles = null; 17 | ArrayList supportedExtensions; 18 | ErrorLevelAnalysisUpdateListener listener; 19 | String outputLabel; 20 | 21 | public ImageStandardizer(File sourceDirectory, File destinationDirectory, Dimension finalResolution, String outLabel) { 22 | System.out.println("Starting new Image Standardizer"); 23 | sourceDir = sourceDirectory; 24 | resolution = finalResolution; 25 | destDir = destinationDirectory; 26 | outputLabel = outLabel; 27 | } 28 | 29 | public void run() { 30 | init(); 31 | loadDirectory(sourceDir.getAbsolutePath()); 32 | processImages(outputLabel); 33 | 34 | } 35 | 36 | public void setListener(ErrorLevelAnalysisUpdateListener listener) { 37 | this.listener = listener; 38 | } 39 | 40 | void init() { 41 | supportedExtensions = new ArrayList<>(Arrays.asList(ConstantObjects.supportedExtensions)); 42 | } 43 | 44 | void processImages(String outLabel) { 45 | System.out.println("Calling Processor with dimension " + resolution); 46 | ErrorLevelAnalyzer imageProcessor 47 | = new ErrorLevelAnalyzer(sourceDir.getAbsolutePath(), destDir.getAbsolutePath(), 95, supportedExtensions, resolution, outLabel); 48 | imageProcessor.setListener(listener); 49 | imageProcessor.addListener(this); 50 | imageProcessor.start(); 51 | } 52 | 53 | public void loadDirectory(String path) { 54 | System.out.println("Loading directory...."); 55 | sourceDir = new File(path); 56 | if (!sourceDir.exists() || sourceDir.isFile()) { 57 | System.out.println("Not a valid directory"); 58 | return; 59 | } 60 | availableFiles = sourceDir.listFiles(); 61 | if (availableFiles == null) { 62 | return; 63 | } 64 | System.out.println("Total " + availableFiles.length + " files are available"); 65 | } 66 | 67 | @Override 68 | public void notifyOfThreadComplete(Thread thread) { 69 | System.out.println("Image Processing Completed"); 70 | System.exit(0); 71 | } 72 | } 73 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/BatchImageTestingListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | public interface BatchImageTestingListener { 4 | 5 | public void testingComplete(String result); 6 | } 7 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/BatchImageTrainingListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | public interface BatchImageTrainingListener { 4 | 5 | public void batchImageTrainingCompleted(); 6 | 7 | public void batchImageTrainingUpdate(int iteration, Double error); 8 | } 9 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/ErrorLevelAnalysisListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | import java.awt.image.BufferedImage; 4 | 5 | public interface ErrorLevelAnalysisListener { 6 | 7 | public void elaCompleted(BufferedImage image); 8 | } 9 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/ErrorLevelAnalysisUpdateListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | public interface ErrorLevelAnalysisUpdateListener { 4 | 5 | public void iterationCompleted(String file, Float percentage); 6 | } 7 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/NeuralNetworkCreationCompleteListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | public interface NeuralNetworkCreationCompleteListener { 4 | 5 | public void networkCreationComplete(Boolean flag); 6 | } 7 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/NeuralnetProcessorListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | import java.util.HashMap; 4 | 5 | public interface NeuralnetProcessorListener { 6 | 7 | public void neuralnetProcessCompleted(HashMap result); 8 | } 9 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/listener/ThreadCompleteListener.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.listener; 2 | 3 | public interface ThreadCompleteListener { 4 | 5 | void notifyOfThreadComplete(final Thread thread); 6 | } 7 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/metadata/MetadataProcessor.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.metadata; 2 | 3 | import com.drew.imaging.ImageMetadataReader; 4 | import com.drew.metadata.Directory; 5 | import com.drew.metadata.Metadata; 6 | import com.drew.metadata.Tag; 7 | import java.io.File; 8 | import java.util.logging.Level; 9 | import java.util.logging.Logger; 10 | 11 | public class MetadataProcessor { 12 | 13 | File imageFile; 14 | public static String extracted_data = ""; 15 | Metadata data = null; 16 | 17 | public MetadataProcessor(File imageFile) { 18 | this.imageFile = imageFile; 19 | try { 20 | data = ImageMetadataReader.readMetadata(imageFile); 21 | } catch (Exception ex) { 22 | Logger.getLogger(MetadataProcessor.class.getName()).log(Level.SEVERE, null, ex); 23 | } 24 | 25 | for (Directory directory : data.getDirectories()) { 26 | extracted_data += String.format("----------------------------------------------%15s---------------------------------\n", directory.getName()); 27 | for (Tag tag : directory.getTags()) { 28 | extracted_data += tag + "\n"; 29 | } 30 | if (directory.hasErrors()) { 31 | for (String error : directory.getErrors()) { 32 | System.err.println("ERROR: " + error); 33 | } 34 | } 35 | } 36 | } 37 | 38 | } 39 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/multithread/NotifyingThread.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.multithread; 2 | 3 | import com.gc.fakeimagedetection.core.listener.ThreadCompleteListener; 4 | import java.util.Set; 5 | import java.util.concurrent.CopyOnWriteArraySet; 6 | 7 | public abstract class NotifyingThread extends Thread { 8 | 9 | private final Set listeners 10 | = new CopyOnWriteArraySet<>(); 11 | 12 | public final void addListener(final ThreadCompleteListener listener) { 13 | listeners.add(listener); 14 | } 15 | 16 | public final void removeListener(final ThreadCompleteListener listener) { 17 | listeners.remove(listener); 18 | } 19 | 20 | private void notifyListeners() { 21 | listeners.stream().forEach((listener) -> { 22 | listener.notifyOfThreadComplete(this); 23 | }); 24 | } 25 | 26 | @Override 27 | public final void run() { 28 | try { 29 | doRun(); 30 | } finally { 31 | notifyListeners(); 32 | } 33 | } 34 | 35 | public abstract void doRun(); 36 | } 37 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/neuralnet/MLPNetworkMaker.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.neuralnet; 2 | 3 | import com.gc.fakeimagedetection.core.listener.NeuralNetworkCreationCompleteListener; 4 | import java.util.List; 5 | import org.neuroph.core.NeuralNetwork; 6 | import org.neuroph.imgrec.ColorMode; 7 | import org.neuroph.imgrec.ImageRecognitionHelper; 8 | import org.neuroph.imgrec.image.Dimension; 9 | import org.neuroph.util.TransferFunctionType; 10 | 11 | public class MLPNetworkMaker implements Runnable { 12 | 13 | String networkLabel; 14 | Dimension samplingDimension; 15 | ColorMode mode; 16 | List outputNeuronLabels; 17 | List neuronCounts; 18 | TransferFunctionType type; 19 | NeuralNetwork nnet; 20 | String saveLocation; 21 | NeuralNetworkCreationCompleteListener listener; 22 | 23 | public void setListener(NeuralNetworkCreationCompleteListener listener) { 24 | this.listener = listener; 25 | } 26 | 27 | public MLPNetworkMaker(String networkLabel, Dimension samplingDimension, ColorMode mode, List outputNeuronLabels, List neuronCounts, TransferFunctionType type, String saveLocation) { 28 | this.networkLabel = networkLabel; 29 | this.samplingDimension = samplingDimension; 30 | this.mode = mode; 31 | this.outputNeuronLabels = outputNeuronLabels; 32 | this.neuronCounts = neuronCounts; 33 | this.type = type; 34 | this.saveLocation = saveLocation; 35 | } 36 | 37 | @Override 38 | public void run() { 39 | Boolean flag = true; 40 | try { 41 | nnet = ImageRecognitionHelper.createNewNeuralNetwork(networkLabel, samplingDimension, mode, outputNeuronLabels, neuronCounts, type); 42 | if (nnet == null) { 43 | throw new Exception("Network Creation Failed"); 44 | } 45 | nnet.save(saveLocation); 46 | } catch (Exception e) { 47 | flag = false; 48 | } 49 | listener.networkCreationComplete(flag); 50 | } 51 | 52 | } 53 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/processor/NeuralNetProcessor.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.processor; 2 | 3 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 4 | import com.gc.fakeimagedetection.core.listener.NeuralnetProcessorListener; 5 | import com.gc.fakeimagedetection.core.multithread.NotifyingThread; 6 | import java.awt.image.BufferedImage; 7 | import java.io.File; 8 | import java.io.FileInputStream; 9 | import java.io.FileNotFoundException; 10 | import java.io.IOException; 11 | import java.util.HashMap; 12 | import java.util.logging.Level; 13 | import java.util.logging.Logger; 14 | import javafx.application.Platform; 15 | import javafx.scene.control.Alert; 16 | import javafx.scene.control.Alert.AlertType; 17 | import javax.imageio.ImageIO; 18 | import org.neuroph.core.NeuralNetwork; 19 | import org.neuroph.imgrec.ImageRecognitionPlugin; 20 | 21 | public class NeuralNetProcessor extends NotifyingThread { 22 | 23 | static BufferedImage image; 24 | public static NeuralNetwork nnet; 25 | static ImageRecognitionPlugin imageRecognition; 26 | NeuralnetProcessorListener listener; 27 | 28 | public void setListener(NeuralnetProcessorListener listener) { 29 | this.listener = listener; 30 | } 31 | 32 | public static void main(String[] args) { 33 | try { 34 | System.out.println("usage java -jar nn.jar image_to_be_processed file_of_neural_network"); 35 | System.out.println("Loading Image...."); 36 | image = ImageIO.read(new File(args[0])); 37 | System.out.println("Loading NN...."); 38 | File NNetwork = new File(args[1]); 39 | if (!NNetwork.exists()) { 40 | System.err.println("Cant Find NN"); 41 | return; 42 | } 43 | nnet = NeuralNetwork.load(new FileInputStream(NNetwork)); // load trained neural network saved with Neuroph Studio 44 | System.out.println("Load Image Recog Plugin...."); 45 | imageRecognition = (ImageRecognitionPlugin) nnet.getPlugin(ImageRecognitionPlugin.class); // get the image recognition plugin from neural network 46 | System.out.println("Recognize Image...."); 47 | HashMap output = imageRecognition.recognizeImage(image); 48 | System.out.println("Output is...."); 49 | System.out.println(output.toString()); 50 | } catch (IOException ex) { 51 | Logger.getLogger(NeuralNetProcessor.class.getName()).log(Level.SEVERE, null, ex); 52 | } 53 | } 54 | 55 | public NeuralNetProcessor(BufferedImage image) { 56 | this.image = image; 57 | } 58 | 59 | void notifyUser() { 60 | Platform.runLater(new Runnable() { 61 | @Override 62 | public void run() { 63 | Alert alert = new Alert(AlertType.ERROR); 64 | alert.setTitle("Neural Network Missing"); 65 | alert.setHeaderText("Cant find network file"); 66 | alert.setContentText("Please make sure that the file " + ConstantObjects.neuralNetworkPath + " exists"); 67 | alert.showAndWait(); 68 | } 69 | }); 70 | } 71 | 72 | @Override 73 | public void doRun() { 74 | try { 75 | //Bypass network reload during comeback through home button 76 | if (nnet == null) { 77 | File NNetwork = new File(ConstantObjects.neuralNetworkPath); 78 | System.out.println("Nueral network loaded = " + NNetwork.getAbsolutePath()); 79 | if (!NNetwork.exists()) { 80 | notifyUser(); 81 | return; 82 | } 83 | nnet = NeuralNetwork.load(new FileInputStream(NNetwork)); // load trained neural network saved with Neuroph Studio 84 | System.out.println("Learning Rule = " + nnet.getLearningRule()); 85 | imageRecognition = (ImageRecognitionPlugin) nnet.getPlugin(ImageRecognitionPlugin.class); // get the image recognition plugin from neural network 86 | } 87 | HashMap output = imageRecognition.recognizeImage(image); 88 | if (output == null) { 89 | System.err.println("Image Recognition Failed"); 90 | } 91 | System.out.println(output.toString()); 92 | listener.neuralnetProcessCompleted(output); 93 | 94 | } catch (Exception ex) { 95 | Logger.getLogger(NeuralNetProcessor.class.getName()).log(Level.SEVERE, null, ex); 96 | listener.neuralnetProcessCompleted(null); 97 | } 98 | } 99 | 100 | } 101 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/tester/BatchImageTestProcessor.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.tester; 2 | 3 | import com.gc.fakeimagedetection.core.listener.BatchImageTestingListener; 4 | import com.gc.fakeimagedetection.ui.alert.Calert; 5 | import java.io.File; 6 | import java.io.FileInputStream; 7 | import java.io.FileNotFoundException; 8 | import java.util.HashMap; 9 | import javafx.scene.control.Alert; 10 | import javax.imageio.ImageIO; 11 | import org.neuroph.core.NeuralNetwork; 12 | import org.neuroph.imgrec.ImageRecognitionPlugin; 13 | 14 | public class BatchImageTestProcessor implements Runnable { 15 | 16 | private int counter = 0; 17 | private int fullSuccess = 0; 18 | private int halfSuccess = 0; 19 | private int error = 0; 20 | private double meanSquareError = 0; 21 | private final File nueralNetwork, realDir, fakeDir; 22 | BatchImageTestingListener listener; 23 | 24 | public BatchImageTestProcessor(File nueralNetwork, File realDir, File fakeDir) { 25 | this.nueralNetwork = nueralNetwork; 26 | this.realDir = realDir; 27 | this.fakeDir = fakeDir; 28 | } 29 | 30 | public void setListener(BatchImageTestingListener listener) { 31 | this.listener = listener; 32 | } 33 | 34 | @Override 35 | public void run() { 36 | if (realDir == null || nueralNetwork == null || fakeDir == null) { 37 | Calert.showAlert("Invalid Data", "Select Required Files", Alert.AlertType.ERROR); 38 | return; 39 | } 40 | 41 | //Load Neural Network 42 | NeuralNetwork network = null; 43 | try { 44 | network = NeuralNetwork.load(new FileInputStream(nueralNetwork)); // load trained neural network saved with Neuroph Studio 45 | } catch (FileNotFoundException ex) { 46 | System.err.println("Neural network failed to load"); 47 | return; 48 | } 49 | System.out.println("Learning Rule = " + network.getLearningRule()); 50 | ImageRecognitionPlugin imageRecognition = (ImageRecognitionPlugin) network.getPlugin(ImageRecognitionPlugin.class); // get the 51 | 52 | //Test Fake Images 53 | for (File fakeImage : fakeDir.listFiles()) { 54 | HashMap output; 55 | try { 56 | output = imageRecognition.recognizeImage(ImageIO.read(fakeImage)); 57 | } catch (Exception ex) { 58 | System.err.println("Image Failed to load" + fakeImage.getAbsolutePath() + ex.getMessage()); 59 | continue; 60 | } 61 | if (output == null) { 62 | System.err.println("Image Recognition Failed"); 63 | continue; 64 | } 65 | counter++; 66 | double real = output.get("real"); 67 | double fake = output.get("faked"); 68 | if (fake >= 0.9 && real < 0.1) { 69 | fullSuccess++; 70 | System.out.println("Required Out : Fake = 1, Real = 0 :: Output Fake = " + fake + " | Real = " + real); 71 | } else if (fake > 0.7) { 72 | halfSuccess++; 73 | System.out.println("Required Out : Fake = 1, Real = 0 :: Output Fake = " + fake + " | Real = " + real); 74 | } else { 75 | System.err.println("Required Out : Fake = 1, Real = 0 :: Output Fake = " + fake + " | Real = " + real + fakeImage.getName()); 76 | } 77 | if (fake < 0.8) { 78 | error++; 79 | } 80 | meanSquareError += ((1 - fake) * (1 - fake)); 81 | } 82 | 83 | //Test Real Images 84 | for (File realImage : realDir.listFiles()) { 85 | HashMap output; 86 | try { 87 | output = imageRecognition.recognizeImage(ImageIO.read(realImage)); 88 | } catch (Exception ex) { 89 | System.err.println("Image Failed to Load " + realImage.getAbsolutePath() + ex.getLocalizedMessage()); 90 | continue; 91 | } 92 | if (output == null) { 93 | System.err.println("Image Recognition Failed"); 94 | continue; 95 | } 96 | counter++; 97 | double real = output.get("real"); 98 | double fake = output.get("faked"); 99 | if (real >= 0.9 && fake < 0.1) { 100 | fullSuccess++; 101 | System.out.println("Required Out : Fake = 0, Real = 1 :: Output Fake = " + fake + " | Real = " + real); 102 | } else if (real > 0.8) { 103 | halfSuccess++; 104 | System.out.println("Required Out : Fake = 0, Real = 1 :: Output Fake = " + fake + " | Real = " + real); 105 | } else { 106 | System.err.println("Required Out : Fake = 0, Real = 1 :: Output Fake = " + fake + " | Real = " + real + realImage.getName()); 107 | } 108 | if (real < 0.8) { 109 | error++; 110 | } 111 | meanSquareError += ((1 - real) * (1 - real)); 112 | } 113 | meanSquareError = meanSquareError / counter; 114 | 115 | String result = ""; 116 | result += ("\n-------------------------------------------------------------------"); 117 | result += ("\nNumber of image processed = " + counter); 118 | result += ("\n100% Correct Detection = " + fullSuccess); 119 | result += ("\nAmbigious Correct Detection = " + halfSuccess); 120 | result += ("\nTotal Error = " + error); 121 | result += ("\nMean Square Error = " + meanSquareError); 122 | result += ("\n-------------------------------------------------------------------"); 123 | System.out.println(result); 124 | listener.testingComplete(result); 125 | } 126 | } 127 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/trainer/BatchImageTrainer.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.trainer; 2 | 3 | import com.gc.fakeimagedetection.core.listener.BatchImageTrainingListener; 4 | import com.gc.fakeimagedetection.core.multithread.NotifyingThread; 5 | import com.gc.fakeimagedetection.ui.alert.Calert; 6 | import java.awt.Dimension; 7 | import java.awt.image.BufferedImage; 8 | import java.io.File; 9 | import java.io.FileInputStream; 10 | import java.io.FileNotFoundException; 11 | import java.util.ArrayList; 12 | import java.util.HashMap; 13 | import java.util.Map; 14 | import javafx.fxml.FXMLLoader; 15 | import javafx.scene.Parent; 16 | import javafx.scene.Scene; 17 | import javafx.scene.control.Alert; 18 | import javafx.stage.Stage; 19 | import org.apache.commons.io.FilenameUtils; 20 | import org.neuroph.core.NeuralNetwork; 21 | import org.neuroph.core.data.DataSet; 22 | import org.neuroph.core.events.LearningEvent; 23 | import org.neuroph.core.events.LearningEventListener; 24 | import org.neuroph.imgrec.FractionRgbData; 25 | import org.neuroph.imgrec.ImageRecognitionHelper; 26 | import org.neuroph.imgrec.ImageUtilities; 27 | import org.neuroph.nnet.learning.BackPropagation; 28 | import org.neuroph.nnet.learning.MomentumBackpropagation; 29 | 30 | public class BatchImageTrainer extends NotifyingThread implements LearningEventListener { 31 | 32 | File srcDirectory; 33 | File nnFile; 34 | Dimension sampleDimension; 35 | ArrayList imageLabels; 36 | NeuralNetwork nnet; 37 | float learningRate = 0f; 38 | float momentum = 0f; 39 | float maxError = 0f; 40 | BatchImageTrainingListener listener; 41 | 42 | public BatchImageTrainer(File srcDirectory, 43 | File nnFile, 44 | Dimension sampleDimension, 45 | ArrayList imageLabels, 46 | BatchImageTrainingListener listener) { 47 | this.srcDirectory = srcDirectory; 48 | this.sampleDimension = sampleDimension; 49 | this.imageLabels = imageLabels; 50 | this.listener = listener; 51 | this.nnFile = nnFile; 52 | } 53 | 54 | public void setMomentum(float momentum) { 55 | this.momentum = momentum; 56 | } 57 | 58 | public void setLearningRate(float learningRate) { 59 | this.learningRate = learningRate; 60 | } 61 | 62 | public void setMaxError(float maxError) { 63 | this.maxError = maxError; 64 | } 65 | 66 | public void stopLearning() { 67 | try { 68 | nnet.stopLearning(); 69 | } catch (Exception e) { 70 | System.out.println(e.getMessage()); 71 | } 72 | } 73 | 74 | public void saveLearnedNetwork(String path) { 75 | try { 76 | nnet.save(path); 77 | Calert.showAlert("Saved", "Neural network saved" + path, Alert.AlertType.INFORMATION); 78 | } catch (Exception e) { 79 | System.err.println("Failed"); 80 | } 81 | } 82 | 83 | @Override 84 | public void doRun() { 85 | try { 86 | System.out.println("Starting training thread....." + sampleDimension.toString() + " and " + imageLabels.toString()); 87 | 88 | HashMap imagesMap = new HashMap(); 89 | for (File file : srcDirectory.listFiles()) { 90 | imageLabels.add(FilenameUtils.removeExtension(file.getName())); 91 | if (sampleDimension.getWidth() > 0 && sampleDimension.getHeight() > 0) { 92 | Double w = sampleDimension.getWidth(); 93 | Double h = sampleDimension.getHeight(); 94 | imagesMap.put(file.getName(), ImageUtilities.resizeImage(ImageUtilities.loadImage(file), w.intValue(), h.intValue())); 95 | } 96 | } 97 | Map imageRgbData = ImageUtilities.getFractionRgbDataForImages(imagesMap); 98 | DataSet learningData = ImageRecognitionHelper.createRGBTrainingSet(imageLabels, imageRgbData); 99 | 100 | nnet = NeuralNetwork.load(new FileInputStream(nnFile)); //Load NNetwork 101 | MomentumBackpropagation mBackpropagation = (MomentumBackpropagation) nnet.getLearningRule(); 102 | mBackpropagation.setLearningRate(learningRate); 103 | mBackpropagation.setMaxError(maxError); 104 | mBackpropagation.setMomentum(momentum); 105 | 106 | System.out.println("Network Information\nLabel = " + nnet.getLabel() 107 | + "\n Input Neurons = " + nnet.getInputsCount() 108 | + "\n Number of layers = " + nnet.getLayersCount() 109 | ); 110 | 111 | mBackpropagation.addListener(this); 112 | System.out.println("Starting training......"); 113 | nnet.learn(learningData, mBackpropagation); 114 | //Training Completed 115 | listener.batchImageTrainingCompleted(); 116 | } catch (FileNotFoundException ex) { 117 | System.out.println(ex.getMessage() + "\n" + ex.getLocalizedMessage()); 118 | } 119 | 120 | } 121 | 122 | @Override 123 | public void handleLearningEvent(LearningEvent event) { 124 | BackPropagation bp = (BackPropagation) event.getSource(); 125 | System.out.println(bp.getCurrentIteration() + ". iteration | Total network error: " + bp.getTotalNetworkError()); 126 | listener.batchImageTrainingUpdate(bp.getCurrentIteration(), bp.getTotalNetworkError()); 127 | } 128 | 129 | private void loadGraph() { 130 | try { 131 | FXMLLoader fxmlLoader = new FXMLLoader(getClass().getResource("/resources/fxml/training_display.fxml")); 132 | Parent root1 = (Parent) fxmlLoader.load(); 133 | Stage stage = new Stage(); 134 | stage.setTitle("Graph View"); 135 | stage.setScene(new Scene(root1)); 136 | stage.show(); 137 | } catch (Exception e) { 138 | System.err.println(e.getMessage()); 139 | } 140 | } 141 | } 142 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/core/trainer/SingleImageTrainer.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.core.trainer; 2 | 3 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 4 | import com.gc.fakeimagedetection.core.processor.NeuralNetProcessor; 5 | import com.gc.fakeimagedetection.core.multithread.NotifyingThread; 6 | import java.awt.image.BufferedImage; 7 | import java.util.ArrayList; 8 | import java.util.HashMap; 9 | import java.util.Map; 10 | import org.neuroph.core.NeuralNetwork; 11 | import org.neuroph.core.data.DataSet; 12 | import org.neuroph.core.events.LearningEvent; 13 | import org.neuroph.core.events.LearningEventListener; 14 | import org.neuroph.imgrec.FractionRgbData; 15 | import org.neuroph.imgrec.ImageRecognitionHelper; 16 | import org.neuroph.imgrec.ImageUtilities; 17 | import org.neuroph.nnet.learning.BackPropagation; 18 | import org.neuroph.nnet.learning.MomentumBackpropagation; 19 | 20 | public class SingleImageTrainer extends NotifyingThread implements LearningEventListener { 21 | 22 | NeuralNetwork nnet; 23 | BufferedImage image; 24 | Boolean isReal; 25 | ArrayList labels; 26 | float learningRate = 0.2f; 27 | float maxError = 0.01f; 28 | float momentum = 0.6f; 29 | public static Boolean isDirty = false; 30 | 31 | public SingleImageTrainer(NeuralNetwork nnet, BufferedImage image, Boolean isReal) { 32 | this.nnet = nnet; 33 | this.image = image; 34 | this.isReal = isReal; 35 | labels = new ArrayList<>(); 36 | labels.add("real"); 37 | labels.add("faked"); 38 | } 39 | 40 | @Override 41 | public void doRun() { 42 | HashMap imagesMap = new HashMap(); 43 | String fileName = ""; 44 | if (!isReal) { 45 | fileName = "real"; 46 | } else { 47 | fileName = "faked"; 48 | } 49 | 50 | System.out.println("Teaching as " + fileName); 51 | imagesMap.put(fileName, image); 52 | Map imageRgbData = ImageUtilities.getFractionRgbDataForImages(imagesMap); 53 | DataSet learningData = ImageRecognitionHelper.createRGBTrainingSet(labels, imageRgbData); 54 | MomentumBackpropagation mBackpropagation = (MomentumBackpropagation) nnet.getLearningRule(); 55 | mBackpropagation.setLearningRate(learningRate); 56 | mBackpropagation.setMaxError(maxError); 57 | mBackpropagation.setMomentum(momentum); 58 | 59 | System.out.println("Network Information\nLabel = " + nnet.getLabel() 60 | + "\n Input Neurons = " + nnet.getInputsCount() 61 | + "\n Number of layers = " + nnet.getLayersCount() 62 | ); 63 | 64 | mBackpropagation.addListener(this); 65 | System.out.println("Starting training......"); 66 | nnet.learn(learningData, mBackpropagation); 67 | 68 | //Mark nnet as dirty. Write on close 69 | isDirty = true; 70 | } 71 | 72 | @Override 73 | public void handleLearningEvent(LearningEvent event) { 74 | BackPropagation bp = (BackPropagation) event.getSource(); 75 | System.out.println(bp.getCurrentIteration() + ". iteration | Total network error: " + bp.getTotalNetworkError()); 76 | } 77 | 78 | } 79 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/BatchImageTester.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui; 2 | 3 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 4 | import javafx.application.Application; 5 | import static javafx.application.Application.launch; 6 | import javafx.fxml.FXMLLoader; 7 | import javafx.scene.Parent; 8 | import javafx.scene.Scene; 9 | import javafx.stage.Stage; 10 | import static javafx.application.Application.launch; 11 | 12 | public class BatchImageTester extends Application { 13 | 14 | @Override 15 | public void start(Stage stage) throws Exception { 16 | Parent root = FXMLLoader.load(getClass().getResource("/resources/fxml/batchimagetester.fxml")); 17 | 18 | Scene scene = new Scene(root); 19 | 20 | stage.resizableProperty().setValue(false); 21 | stage.setTitle("Batch Image Tester"); 22 | stage.setScene(scene); 23 | CommonUtil.attachIcon(stage); 24 | stage.show(); 25 | } 26 | 27 | public static void main(String[] args) { 28 | launch(args); 29 | } 30 | 31 | } 32 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/ELABatchImageProcessor.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui; 2 | 3 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 4 | import javafx.application.Application; 5 | import javafx.fxml.FXMLLoader; 6 | import javafx.scene.Parent; 7 | import javafx.scene.Scene; 8 | import javafx.stage.Stage; 9 | import static javafx.application.Application.launch; 10 | 11 | public class ELABatchImageProcessor extends Application { 12 | 13 | @Override 14 | public void start(Stage stage) throws Exception { 15 | Parent root = FXMLLoader.load(getClass().getResource("/resources/fxml/batchimageprocessor.fxml")); 16 | 17 | Scene scene = new Scene(root); 18 | 19 | stage.resizableProperty().setValue(false); 20 | stage.setTitle("Batch ELA processor"); 21 | stage.setScene(scene); 22 | CommonUtil.attachIcon(stage); 23 | stage.show(); 24 | } 25 | 26 | public static void main(String[] args) { 27 | launch(args); 28 | } 29 | 30 | } 31 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/Main.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui; 2 | 3 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 4 | import com.gc.fakeimagedetection.core.processor.NeuralNetProcessor; 5 | import com.gc.fakeimagedetection.core.trainer.SingleImageTrainer; 6 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 7 | import java.util.Optional; 8 | import javafx.application.Application; 9 | import javafx.fxml.FXMLLoader; 10 | import javafx.scene.Parent; 11 | import javafx.scene.Scene; 12 | import javafx.scene.control.Alert; 13 | import javafx.scene.control.Alert.AlertType; 14 | import javafx.scene.control.ButtonType; 15 | import javafx.scene.image.Image; 16 | import javafx.stage.Stage; 17 | import javafx.stage.WindowEvent; 18 | 19 | public class Main extends Application { 20 | 21 | @Override 22 | public void start(Stage stage) throws Exception { 23 | Parent root = FXMLLoader.load(getClass().getResource("/resources/fxml/launch.fxml")); 24 | 25 | Scene scene = new Scene(root); 26 | 27 | stage.setTitle("Christopher"); 28 | stage.setScene(scene); 29 | stage.show(); 30 | CommonUtil.attachIcon(stage); 31 | stage.setOnCloseRequest((WindowEvent event) -> { 32 | if (SingleImageTrainer.isDirty) { 33 | Alert alert = new Alert(AlertType.CONFIRMATION); 34 | alert.setTitle("Save Changes ?"); 35 | alert.setHeaderText("Neural Network has been updated with new data"); 36 | alert.setContentText("Do you want to save changes ?"); 37 | Optional result = alert.showAndWait(); 38 | if (result.get() == ButtonType.OK) { 39 | NeuralNetProcessor.nnet.save(ConstantObjects.neuralNetworkPath); 40 | System.out.println("Saved to " + ConstantObjects.neuralNetworkPath); 41 | System.exit(0); 42 | } else { 43 | System.out.println("Changes discared"); 44 | System.exit(1); 45 | } 46 | } 47 | }); 48 | } 49 | 50 | public static void main(String[] args) { 51 | launch(args); 52 | } 53 | 54 | } 55 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/NeuralNetCreator.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui; 2 | 3 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 4 | import javafx.application.Application; 5 | import javafx.fxml.FXMLLoader; 6 | import javafx.scene.Parent; 7 | import javafx.scene.Scene; 8 | import javafx.stage.Stage; 9 | import javafx.stage.WindowEvent; 10 | import static javafx.application.Application.launch; 11 | 12 | public class NeuralNetCreator extends Application { 13 | 14 | @Override 15 | public void start(Stage stage) throws Exception { 16 | Parent root = FXMLLoader.load(getClass().getResource("/resources/fxml/networkcreator.fxml")); 17 | 18 | Scene scene = new Scene(root); 19 | 20 | stage.resizableProperty().setValue(false); 21 | stage.setTitle("Neural Network Creator"); 22 | stage.setScene(scene); 23 | stage.show(); 24 | CommonUtil.attachIcon(stage); 25 | 26 | stage.setOnCloseRequest((WindowEvent event) -> { 27 | System.exit(0); 28 | }); 29 | } 30 | 31 | public static void main(String[] args) { 32 | launch(args); 33 | } 34 | 35 | } 36 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/SingleImageCheck.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui; 2 | 3 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 4 | import javafx.application.Application; 5 | import static javafx.application.Application.launch; 6 | import javafx.fxml.FXMLLoader; 7 | import javafx.scene.Parent; 8 | import javafx.scene.Scene; 9 | import javafx.stage.Stage; 10 | import javafx.stage.WindowEvent; 11 | import static javafx.application.Application.launch; 12 | 13 | public class SingleImageCheck extends Application { 14 | 15 | @Override 16 | public void start(Stage stage) throws Exception { 17 | Parent root = FXMLLoader.load(getClass().getResource("/resources/fxml/singleimage.fxml")); 18 | 19 | Scene scene = new Scene(root); 20 | 21 | stage.resizableProperty().setValue(false); 22 | stage.setTitle("Single Image Checker"); 23 | stage.setScene(scene); 24 | stage.show(); 25 | CommonUtil.attachIcon(stage); 26 | 27 | stage.setOnCloseRequest((WindowEvent event) -> { 28 | System.exit(0); 29 | }); 30 | } 31 | 32 | public static void main(String[] args) { 33 | launch(args); 34 | } 35 | 36 | } 37 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/TrainerMain.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui; 2 | 3 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 4 | import javafx.application.Application; 5 | import javafx.fxml.FXMLLoader; 6 | import javafx.scene.Parent; 7 | import javafx.scene.Scene; 8 | import javafx.stage.Stage; 9 | import javafx.stage.WindowEvent; 10 | import static javafx.application.Application.launch; 11 | 12 | public class TrainerMain extends Application { 13 | 14 | @Override 15 | public void start(Stage stage) throws Exception { 16 | Parent root = FXMLLoader.load(getClass().getResource("/resources/fxml/traininginterface.fxml")); 17 | 18 | Scene scene = new Scene(root); 19 | 20 | stage.resizableProperty().setValue(false); 21 | stage.setTitle("Network Trainer"); 22 | stage.setScene(scene); 23 | stage.show(); 24 | CommonUtil.attachIcon(stage); 25 | 26 | stage.setOnCloseRequest((WindowEvent event) -> { 27 | System.exit(0); 28 | }); 29 | } 30 | 31 | public static void main(String[] args) { 32 | launch(args); 33 | } 34 | 35 | } 36 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/alert/Calert.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.alert; 2 | 3 | import javafx.scene.control.Alert; 4 | 5 | public class Calert { 6 | 7 | public static void showAlert(String title, String Content, Alert.AlertType alertType) { 8 | Alert alert = new Alert(alertType); 9 | alert.setTitle(title); 10 | alert.setHeaderText(null); 11 | alert.setContentText(Content); 12 | alert.showAndWait(); 13 | } 14 | } 15 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/alert/CommonUtil.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.alert; 2 | 3 | import com.gc.fakeimagedetection.ui.Main; 4 | import javafx.scene.image.Image; 5 | import javafx.stage.Stage; 6 | 7 | public class CommonUtil { 8 | 9 | private static final String ICON = "/resources/icon/icon.png"; 10 | 11 | public static void attachIcon(Stage stage) { 12 | stage.getIcons().add(new Image(Main.class.getResourceAsStream(ICON))); 13 | } 14 | } 15 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/BatchImageProcessorController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXCheckBox; 4 | import com.jfoenix.controls.JFXTextField; 5 | import com.gc.fakeimagedetection.ui.alert.Calert; 6 | import com.gc.fakeimagedetection.core.errorlevelanalysis.ImageStandardizer; 7 | import com.gc.fakeimagedetection.core.listener.ErrorLevelAnalysisUpdateListener; 8 | import java.awt.Dimension; 9 | import java.io.File; 10 | import java.net.URL; 11 | import java.util.ResourceBundle; 12 | import javafx.event.ActionEvent; 13 | import javafx.fxml.FXML; 14 | import javafx.fxml.Initializable; 15 | import javafx.scene.control.Alert; 16 | import javafx.scene.control.ProgressBar; 17 | import javafx.scene.layout.AnchorPane; 18 | import javafx.scene.text.Text; 19 | import javafx.stage.DirectoryChooser; 20 | 21 | public class BatchImageProcessorController implements Initializable, ErrorLevelAnalysisUpdateListener { 22 | 23 | @FXML 24 | private JFXCheckBox srcIndicator; 25 | @FXML 26 | private JFXTextField sWidth; 27 | @FXML 28 | private JFXTextField sHeight; 29 | @FXML 30 | private JFXTextField outputBatchName; 31 | @FXML 32 | private JFXCheckBox destIndicator; 33 | @FXML 34 | private ProgressBar progressBar; 35 | 36 | File srcDir = null; 37 | File destDir = null; 38 | @FXML 39 | private AnchorPane rootPane; 40 | 41 | private String bName = "real_"; 42 | @FXML 43 | private Text status; 44 | 45 | @Override 46 | public void initialize(URL url, ResourceBundle rb) { 47 | } 48 | 49 | @FXML 50 | private void loadSourceFolder(ActionEvent event) { 51 | DirectoryChooser chooser = new DirectoryChooser(); 52 | chooser.setTitle("Choose Source Folder"); 53 | srcDir = chooser.showDialog(rootPane.getScene().getWindow()); 54 | if (srcDir == null) { 55 | Calert.showAlert("Error", "Not a valid folder", Alert.AlertType.ERROR); 56 | return; 57 | } 58 | srcIndicator.setSelected(true); 59 | } 60 | 61 | @FXML 62 | private void loadDestinationFolder(ActionEvent event) { 63 | DirectoryChooser chooser = new DirectoryChooser(); 64 | chooser.setTitle("Choose Source Folder"); 65 | destDir = chooser.showDialog(rootPane.getScene().getWindow()); 66 | if (destDir == null) { 67 | Calert.showAlert("Error", "Not a valid folder", Alert.AlertType.ERROR); 68 | return; 69 | } 70 | destIndicator.setSelected(true); 71 | } 72 | 73 | @FXML 74 | private void startProcessing(ActionEvent event) { 75 | int width = Integer.parseInt(sWidth.getText()); 76 | int height = Integer.parseInt(sHeight.getText()); 77 | bName = outputBatchName.getText(); 78 | if (srcDir != null && destDir != null) { 79 | ImageStandardizer ims = new ImageStandardizer(srcDir, destDir, new Dimension(width, height), bName); 80 | ims.setListener(this); 81 | ims.run(); 82 | } else { 83 | System.out.println("Source Not selected"); 84 | } 85 | } 86 | 87 | @Override 88 | public void iterationCompleted(String data, Float percentage) { 89 | status.setText(data); 90 | progressBar.setProgress(percentage); 91 | } 92 | 93 | } 94 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/BatchImageTesterController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.jfoenix.controls.JFXCheckBox; 5 | import com.jfoenix.controls.JFXSpinner; 6 | import com.gc.fakeimagedetection.core.listener.BatchImageTestingListener; 7 | import com.gc.fakeimagedetection.core.tester.BatchImageTestProcessor; 8 | import com.gc.fakeimagedetection.ui.alert.Calert; 9 | import java.io.File; 10 | import java.net.URL; 11 | import java.util.ResourceBundle; 12 | import javafx.application.Platform; 13 | import javafx.event.ActionEvent; 14 | import javafx.fxml.FXML; 15 | import javafx.fxml.Initializable; 16 | import javafx.scene.control.Alert; 17 | import javafx.scene.layout.AnchorPane; 18 | import javafx.stage.DirectoryChooser; 19 | import javafx.stage.FileChooser; 20 | 21 | public class BatchImageTesterController implements Initializable, BatchImageTestingListener { 22 | 23 | @FXML 24 | private JFXCheckBox neuralIndicator; 25 | @FXML 26 | private JFXCheckBox realIndicator; 27 | @FXML 28 | private JFXCheckBox fakeIndicator; 29 | @FXML 30 | private AnchorPane rootPane; 31 | @FXML 32 | private JFXButton startButton; 33 | 34 | File neuralNetwork; 35 | File realDir; 36 | File fakeDir; 37 | @FXML 38 | private JFXSpinner spinner; 39 | 40 | @Override 41 | public void initialize(URL url, ResourceBundle rb) { 42 | spinner.setVisible(false); 43 | } 44 | 45 | @FXML 46 | private void chooseNeuralNetwork(ActionEvent event) { 47 | FileChooser chooser = new FileChooser(); 48 | chooser.setTitle("Choose Neuralnet"); 49 | neuralNetwork = chooser.showOpenDialog(rootPane.getScene().getWindow()); 50 | if (neuralNetwork == null) { 51 | Calert.showAlert("Error", "Not a valid neural network", Alert.AlertType.ERROR); 52 | return; 53 | } 54 | 55 | System.out.println("Loading Neuralnet from " + neuralNetwork.getAbsolutePath()); 56 | neuralIndicator.setSelected(true); 57 | } 58 | 59 | @FXML 60 | private void chooseRealImageSource(ActionEvent event) { 61 | DirectoryChooser chooser = new DirectoryChooser(); 62 | chooser.setTitle("Choose Real Image Folder"); 63 | realDir = chooser.showDialog(rootPane.getScene().getWindow()); 64 | if (realDir == null) { 65 | Calert.showAlert("Error", "Not a valid directory", Alert.AlertType.ERROR); 66 | return; 67 | } 68 | 69 | System.out.println("Loading Real Images from " + realDir.getAbsolutePath()); 70 | realIndicator.setSelected(true); 71 | } 72 | 73 | @FXML 74 | private void chooseFakeImageSource(ActionEvent event) { 75 | DirectoryChooser chooser = new DirectoryChooser(); 76 | chooser.setTitle("Choose Fake Image Folder"); 77 | fakeDir = chooser.showDialog(rootPane.getScene().getWindow()); 78 | if (fakeDir == null) { 79 | Calert.showAlert("Error", "Not a valid directory", Alert.AlertType.ERROR); 80 | return; 81 | } 82 | 83 | System.out.println("Loading Fake Images from " + realDir.getAbsolutePath()); 84 | fakeIndicator.setSelected(true); 85 | } 86 | 87 | @FXML 88 | private void startTesting(ActionEvent event) { 89 | startButton.setText("Running..."); 90 | BatchImageTestProcessor processor = new BatchImageTestProcessor(neuralNetwork, realDir, fakeDir); 91 | processor.setListener(this); 92 | Thread runnerThread = new Thread(processor); 93 | runnerThread.start(); 94 | spinner.setVisible(true); 95 | } 96 | 97 | void updateText(String text) { 98 | Platform.runLater(new Runnable() { 99 | @Override 100 | public void run() { 101 | startButton.setText(text); 102 | } 103 | }); 104 | } 105 | 106 | void showResult(String result) { 107 | Platform.runLater(new Runnable() { 108 | @Override 109 | public void run() { 110 | Calert.showAlert("Result", result, Alert.AlertType.INFORMATION); 111 | } 112 | }); 113 | } 114 | 115 | @Override 116 | public void testingComplete(String result) { 117 | spinner.setVisible(false); 118 | showResult(result); 119 | updateText("Completed"); 120 | } 121 | } 122 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/LaunchScreeenController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 5 | import com.gc.fakeimagedetection.ui.alert.Calert; 6 | import com.gc.fakeimagedetection.core.metadata.MetadataProcessor; 7 | import com.gc.fakeimagedetection.ui.BatchImageTester; 8 | import com.gc.fakeimagedetection.ui.ELABatchImageProcessor; 9 | import com.gc.fakeimagedetection.ui.SingleImageCheck; 10 | import com.gc.fakeimagedetection.ui.TrainerMain; 11 | import java.io.File; 12 | import java.io.FileInputStream; 13 | import java.io.IOException; 14 | import java.net.URL; 15 | import java.util.ResourceBundle; 16 | import java.util.logging.Level; 17 | import java.util.logging.Logger; 18 | import javafx.animation.KeyFrame; 19 | import javafx.animation.KeyValue; 20 | import javafx.animation.ParallelTransition; 21 | import javafx.animation.ScaleTransition; 22 | import javafx.animation.Timeline; 23 | import javafx.animation.TranslateTransition; 24 | import javafx.event.ActionEvent; 25 | import javafx.fxml.FXML; 26 | import javafx.fxml.FXMLLoader; 27 | import javafx.fxml.Initializable; 28 | import javafx.scene.control.Alert.AlertType; 29 | import javafx.scene.control.CheckMenuItem; 30 | import javafx.scene.image.Image; 31 | import javafx.scene.image.ImageView; 32 | import javafx.scene.input.MouseEvent; 33 | import javafx.scene.layout.AnchorPane; 34 | import javafx.scene.layout.BorderPane; 35 | import javafx.scene.layout.StackPane; 36 | import javafx.scene.text.Font; 37 | import javafx.scene.text.FontWeight; 38 | import javafx.scene.text.Text; 39 | import javafx.stage.FileChooser; 40 | import javafx.stage.Modality; 41 | import javafx.stage.Stage; 42 | import javafx.stage.WindowEvent; 43 | import javafx.util.Duration; 44 | 45 | public class LaunchScreeenController implements Initializable { 46 | 47 | @FXML 48 | private JFXButton load_image_button; 49 | 50 | @FXML 51 | private Text christopher; 52 | 53 | @FXML 54 | private StackPane rootPane; 55 | 56 | @FXML 57 | private Text description; 58 | 59 | @FXML 60 | private AnchorPane anchorPane; 61 | 62 | @FXML 63 | private ImageView homeIcon; 64 | @FXML 65 | private ImageView backgroundImageView; 66 | 67 | int duration = 1500; 68 | FileChooser fileChooser; 69 | Boolean isFirstTime = true; 70 | ScaleTransition bulgingTransition; 71 | ParallelTransition buttonParallelTransition; 72 | public static File processingFile = null; 73 | public static StackPane parentPaneForAll; 74 | @FXML 75 | private CheckMenuItem resultPropogation; 76 | 77 | @Override 78 | public void initialize(URL url, ResourceBundle rb) { 79 | parentPaneForAll = rootPane; 80 | 81 | } 82 | 83 | private void animate() { 84 | TranslateTransition tt = new TranslateTransition(Duration.millis(duration), load_image_button); 85 | TranslateTransition tLogo = new TranslateTransition(Duration.millis(duration), christopher); 86 | TranslateTransition tDesc = new TranslateTransition(Duration.millis(duration), description); 87 | 88 | ScaleTransition st = new ScaleTransition(Duration.millis(duration), load_image_button); 89 | st.setToX(3); 90 | st.setToY(3); 91 | 92 | tt.setByY(-180f); 93 | 94 | tLogo.setToY(50); 95 | tDesc.setToY(500); 96 | buttonParallelTransition = new ParallelTransition(load_image_button, st, tt, tLogo, tDesc); 97 | 98 | buttonParallelTransition.play(); 99 | buttonParallelTransition.setOnFinished((e) -> { 100 | load_image_button.setOpacity(1); 101 | }); 102 | } 103 | 104 | @FXML 105 | private void loadAnimation(MouseEvent event) { 106 | if (isFirstTime) { 107 | animate(); 108 | isFirstTime = false; 109 | } 110 | } 111 | 112 | @FXML 113 | void loadImageSelector(ActionEvent event) { 114 | if (processingFile != null) { 115 | return; 116 | } 117 | fileChooser = new FileChooser(); 118 | configureFileChooser(fileChooser); 119 | fileChooser.setTitle("Open Resource File"); 120 | processingFile = fileChooser.showOpenDialog(rootPane.getScene().getWindow()); 121 | if (processingFile == null) { 122 | Calert.showAlert("No File Selected", "You haven't selected any images", AlertType.ERROR); 123 | return; 124 | } 125 | 126 | try { 127 | backgroundImageView.setImage(new Image(new FileInputStream(processingFile))); 128 | backgroundImageView.setOpacity(0.5); 129 | } catch (Exception ex) { 130 | Logger.getLogger(LaunchScreeenController.class.getName()).log(Level.SEVERE, null, ex); 131 | } 132 | removeBannersandDescs(); 133 | loadMetaDataCheck(); 134 | } 135 | 136 | private static void configureFileChooser(final FileChooser fileChooser) { 137 | fileChooser.setTitle("View Pictures"); 138 | fileChooser.setInitialDirectory( 139 | new File(System.getProperty("user.dir")) 140 | ); 141 | FileChooser.ExtensionFilter extFilter 142 | = new FileChooser.ExtensionFilter("Image Files", "*.JPG", "*.jpg", "*.jpeg", "*.JPEG"); 143 | fileChooser.getExtensionFilters().addAll(extFilter 144 | ); 145 | 146 | } 147 | 148 | private void removeBannersandDescs() { 149 | TranslateTransition tChristopher = new TranslateTransition(Duration.millis(duration), christopher); 150 | TranslateTransition tDescription = new TranslateTransition(Duration.millis(duration), description); 151 | tChristopher.setToY(-200); 152 | tDescription.setToY(1000); 153 | ParallelTransition pt = new ParallelTransition(tChristopher, tDescription); 154 | pt.play(); 155 | 156 | } 157 | 158 | private void loadMetaDataCheck() { 159 | startSimpleMetaDataAnimation(); 160 | 161 | MetadataProcessor processor = new MetadataProcessor(processingFile); 162 | 163 | bulgingTransition.setOnFinished((e) -> { 164 | TranslateTransition tt = new TranslateTransition(Duration.millis(duration - 500), load_image_button); 165 | ScaleTransition st = new ScaleTransition(Duration.millis(duration - 500), load_image_button); 166 | st.setToX(1); 167 | st.setToY(1); 168 | 169 | tt.setToX(-150f); 170 | tt.setToY(80f); 171 | 172 | Timeline timeline = new Timeline(); 173 | timeline.setCycleCount(1); 174 | 175 | KeyValue keyValueX = new KeyValue(load_image_button.prefWidthProperty(), 400); 176 | KeyValue keyValueY = new KeyValue(load_image_button.prefHeightProperty(), 50); 177 | KeyFrame keyFrame = new KeyFrame(Duration.millis(duration - 500), keyValueX, keyValueY); 178 | timeline.getKeyFrames().add(keyFrame); 179 | 180 | ParallelTransition pt = new ParallelTransition(load_image_button, st, tt, timeline); 181 | pt.play(); 182 | 183 | pt.setOnFinished((e1) -> { 184 | loadMetadataResult(); 185 | load_image_button.setText("Test On AI"); 186 | load_image_button.setFont(Font.font("Roboto", FontWeight.BOLD, 20)); 187 | homeIcon.setVisible(true); 188 | // Neural Network Entry 189 | load_image_button.setOnMouseClicked((e2) -> { 190 | System.out.println("Loading NN........"); 191 | try { 192 | anchorPane.getChildren().clear(); 193 | StackPane pane = FXMLLoader.load(getClass().getResource("/resources/fxml/neuralinterface.fxml")); 194 | anchorPane.getChildren().setAll(pane); 195 | } catch (IOException ex) { 196 | Logger.getLogger(MetadataResultController.class.getName()).log(Level.SEVERE, null, ex); 197 | } 198 | }); 199 | }); 200 | }); 201 | 202 | } 203 | 204 | private void startSimpleMetaDataAnimation() { 205 | float animationExtension = 3.25f; 206 | bulgingTransition = new ScaleTransition(Duration.millis(1000), load_image_button); 207 | bulgingTransition.setToX(animationExtension); 208 | bulgingTransition.setToY(animationExtension); 209 | bulgingTransition.autoReverseProperty().setValue(true); 210 | bulgingTransition.setCycleCount(2); 211 | bulgingTransition.play(); 212 | load_image_button.setFont(Font.font("Roboto", FontWeight.NORMAL, 8)); 213 | load_image_button.setText("Checking Metadata.."); 214 | 215 | } 216 | 217 | private void loadMetadataResult() { 218 | try { 219 | AnchorPane result = FXMLLoader.load(getClass().getResource("/resources/fxml/metadataresult.fxml")); 220 | anchorPane.getChildren().add(result); 221 | } catch (IOException ex) { 222 | Logger.getLogger(LaunchScreeenController.class.getName()).log(Level.SEVERE, null, ex); 223 | } 224 | } 225 | 226 | @FXML 227 | private void rollBack(MouseEvent event) { 228 | processingFile = null; 229 | try { 230 | BorderPane pane = FXMLLoader.load(getClass().getResource("/resources/fxml/launch.fxml")); 231 | rootPane.getChildren().clear(); 232 | rootPane.getChildren().setAll(pane); 233 | MetadataProcessor.extracted_data = ""; 234 | } catch (IOException ex) { 235 | Logger.getLogger(LaunchScreeenController.class.getName()).log(Level.SEVERE, null, ex); 236 | } 237 | } 238 | 239 | @FXML 240 | private void loadELAProcessor(ActionEvent event) throws Exception { 241 | ELABatchImageProcessor processor = new ELABatchImageProcessor(); 242 | Stage stage = new Stage(); 243 | stage.initOwner(rootPane.getScene().getWindow()); 244 | stage.initModality(Modality.WINDOW_MODAL); 245 | processor.start(stage); 246 | } 247 | 248 | @FXML 249 | private void loadTrainer(ActionEvent event) throws Exception { 250 | TrainerMain trainer = new TrainerMain(); 251 | Stage stage = new Stage(); 252 | stage.initOwner(rootPane.getScene().getWindow()); 253 | stage.initModality(Modality.APPLICATION_MODAL); 254 | trainer.start(stage); 255 | stage.setOnCloseRequest((WindowEvent event1) -> { 256 | event1.consume(); 257 | stage.close(); 258 | }); 259 | } 260 | 261 | @FXML 262 | private void loadBatchImageTester(ActionEvent event) throws Exception { 263 | BatchImageTester tester = new BatchImageTester(); 264 | Stage stage = new Stage(); 265 | stage.initOwner(rootPane.getScene().getWindow()); 266 | stage.initModality(Modality.WINDOW_MODAL); 267 | tester.start(stage); 268 | } 269 | 270 | @FXML 271 | private void loadSingleImageTester(ActionEvent event) throws Exception { 272 | SingleImageCheck siCheck = new SingleImageCheck(); 273 | Stage stage = new Stage(); 274 | stage.initOwner(rootPane.getScene().getWindow()); 275 | stage.initModality(Modality.WINDOW_MODAL); 276 | siCheck.start(stage); 277 | stage.setOnCloseRequest((WindowEvent event1) -> { 278 | event1.consume(); 279 | stage.close(); 280 | }); 281 | } 282 | 283 | @FXML 284 | private void loadFullScreen(ActionEvent event) { 285 | Stage stage = (Stage) rootPane.getScene().getWindow(); 286 | stage.setFullScreen(true); 287 | } 288 | 289 | @FXML 290 | private void changeResultPropogation(ActionEvent event) { 291 | ConstantObjects.shouldPropogateResult = resultPropogation.isSelected(); 292 | } 293 | 294 | } 295 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/MetadataDisplayController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.jfoenix.controls.JFXTextArea; 5 | import com.gc.fakeimagedetection.core.metadata.MetadataProcessor; 6 | import java.net.URL; 7 | import java.util.ResourceBundle; 8 | import javafx.event.ActionEvent; 9 | import javafx.fxml.FXML; 10 | import javafx.fxml.Initializable; 11 | import javafx.stage.Stage; 12 | 13 | public class MetadataDisplayController implements Initializable { 14 | 15 | @FXML 16 | private JFXTextArea displayField; 17 | @FXML 18 | private JFXButton closeButton; 19 | 20 | @Override 21 | public void initialize(URL url, ResourceBundle rb) { 22 | displayField.setText(MetadataProcessor.extracted_data); 23 | } 24 | 25 | @FXML 26 | private void closeWindow(ActionEvent event) { 27 | Stage stage = (Stage) closeButton.getScene().getWindow(); 28 | stage.close(); 29 | } 30 | 31 | } 32 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/MetadataResultController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.jfoenix.controls.JFXSnackbar; 5 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 6 | import com.gc.fakeimagedetection.core.metadata.MetadataProcessor; 7 | import com.gc.fakeimagedetection.ui.alert.CommonUtil; 8 | import java.io.IOException; 9 | import java.net.URL; 10 | import java.util.ArrayList; 11 | import java.util.ResourceBundle; 12 | import java.util.logging.Level; 13 | import java.util.logging.Logger; 14 | import javafx.collections.FXCollections; 15 | import javafx.collections.ObservableList; 16 | import javafx.event.ActionEvent; 17 | import javafx.event.EventHandler; 18 | import javafx.fxml.FXML; 19 | import javafx.fxml.FXMLLoader; 20 | import javafx.fxml.Initializable; 21 | import javafx.scene.Node; 22 | import javafx.scene.Parent; 23 | import javafx.scene.Scene; 24 | import javafx.scene.chart.PieChart; 25 | import javafx.scene.control.Label; 26 | import javafx.scene.input.MouseEvent; 27 | import javafx.scene.layout.AnchorPane; 28 | import javafx.scene.paint.Color; 29 | import javafx.stage.Modality; 30 | import javafx.stage.Stage; 31 | import javafx.stage.StageStyle; 32 | 33 | public class MetadataResultController implements Initializable { 34 | 35 | @FXML 36 | private PieChart pie_chart; 37 | 38 | ObservableList pieChartData; 39 | @FXML 40 | private AnchorPane anchorPane; 41 | @FXML 42 | private JFXButton resultButton; 43 | 44 | MetadataDisplayController metadata_display_controller; 45 | int fakeness = 1; 46 | int real = 1; 47 | String output = ""; 48 | String fakeReason = ""; 49 | String realReason = ""; 50 | 51 | @Override 52 | public void initialize(URL url, ResourceBundle rb) { 53 | generatePercentage(); 54 | processResult(); 55 | 56 | } 57 | 58 | private void processResult() { 59 | String extractedData = MetadataProcessor.extracted_data; 60 | ArrayList components = new ArrayList<>(); 61 | for (String component : extractedData.split("\n")) { 62 | components.add(component); 63 | } 64 | 65 | if (extractedData.contains("Photoshop") || extractedData.contains("PHOTOSHOP")) { 66 | String version = ""; 67 | for (String component : components) { 68 | if (component.contains("Adobe Photoshop")) { 69 | try { 70 | version = component.substring(component.indexOf('A')); 71 | } catch (Exception e) { 72 | } 73 | } 74 | } 75 | if (version.length() < 2) { 76 | resultButton.setText("Fake Image With Adobe Tag\n"); 77 | } else { 78 | resultButton.setText("Tampered With\n" + version.replaceAll("[(,)]", "")); 79 | } 80 | resultButton.setStyle("-fx-background-color:#ff0000"); 81 | } else if (extractedData.contains("Gimp") || extractedData.contains("GIMP")) { 82 | resultButton.setText("Tampered With Gimp"); 83 | resultButton.setStyle("-fx-background-color:#ff0000"); 84 | } else if (real > fakeness) { 85 | if (fakeness < 3) { 86 | resultButton.setText("Seems like Real Camera Image"); 87 | resultButton.setStyle("-fx-background-color:#64DD17"); 88 | } else { 89 | resultButton.setText("Metadata Is Clean"); 90 | resultButton.setStyle("-fx-background-color:#64DD17"); 91 | } 92 | } else if (real == fakeness) { 93 | resultButton.setText("Cant Determine. Proceed with AI"); 94 | resultButton.setStyle("-fx-background-color:#455A64"); 95 | } else { 96 | resultButton.setText("Digitally Altered. Not from Camera"); 97 | resultButton.setStyle("-fx-background-color:#FF5722"); 98 | } 99 | 100 | if (extractedData.contains("Original Transmission Reference") && extractedData.contains("Special Instructions")) { 101 | JFXSnackbar snackbar = new JFXSnackbar(anchorPane); 102 | snackbar.getStylesheets().add(getClass().getResource("/resources/stylesheets/main.css").toExternalForm()); 103 | snackbar.show("Downloaded Image From Facebook", 10000); 104 | } 105 | if (extractedData.contains("Software - Google")) { 106 | JFXSnackbar snackbar = new JFXSnackbar(anchorPane); 107 | snackbar.getStylesheets().add(getClass().getResource("/resources/stylesheets/main.css").toExternalForm()); 108 | snackbar.show("Tampered By Google. May be from Google+", 10000); 109 | } 110 | 111 | } 112 | 113 | void displayMetaData() { 114 | try { 115 | FXMLLoader fxmlLoader = new FXMLLoader(getClass().getResource("/resources/fxml/metadatadisplay.fxml")); 116 | Parent root1 = (Parent) fxmlLoader.load(); 117 | metadata_display_controller = fxmlLoader.getController(); 118 | Stage stage = new Stage(); 119 | stage.initModality(Modality.WINDOW_MODAL); 120 | stage.resizableProperty().set(false); 121 | stage.setTitle("Metadata Information"); 122 | stage.setScene(new Scene(root1)); 123 | CommonUtil.attachIcon(stage); 124 | stage.show(); 125 | } catch (Exception e) { 126 | 127 | } 128 | } 129 | 130 | @FXML 131 | private void displayMoreInfo(ActionEvent event) { 132 | displayMetaData(); 133 | } 134 | 135 | private void generatePercentage() { 136 | real = 1; 137 | fakeness = 1; 138 | realReason = "Contains "; 139 | String extractedData = MetadataProcessor.extracted_data; 140 | ArrayList componentsToCheck = new ArrayList<>(); 141 | componentsToCheck.add("Exif IFD0"); 142 | componentsToCheck.add("Exif SubIFD"); 143 | componentsToCheck.add("Interoperability"); 144 | componentsToCheck.add("Exif Thumbnail"); 145 | componentsToCheck.add("Model"); 146 | componentsToCheck.add("Make"); 147 | componentsToCheck.add("Exposure Time "); 148 | componentsToCheck.add("F-Number"); 149 | componentsToCheck.add("Flash"); 150 | componentsToCheck.add("Focal Length"); 151 | for (String string : componentsToCheck) { 152 | if (extractedData.contains(string)) { 153 | real++; 154 | realReason += string + ","; 155 | if (real % 5 == 0) { 156 | realReason += "\n"; 157 | } 158 | } 159 | } 160 | realReason = realReason.substring(0, realReason.length() - 1); //Remove last Comma 161 | 162 | int ctr = 0; 163 | for (String string : MetadataProcessor.extracted_data.split("\n")) { 164 | ctr++; 165 | if (string.toUpperCase().contains("ADOBE")) { 166 | fakeness += 6; 167 | if (!fakeReason.contains("Detected Adobe Tag")) { 168 | fakeReason += "Detected Adobe Tag" + "\n"; 169 | } 170 | } 171 | if (string.toUpperCase().contains("PHOTOSHOP")) { 172 | fakeness += 15; 173 | if (!fakeReason.contains("Detected Photoshop Tag")) { 174 | fakeReason += "Detected Photoshop Tag" + "\n"; 175 | } 176 | } 177 | if (string.toUpperCase().contains("GIMP")) { 178 | fakeness += 15; 179 | if (!fakeReason.contains("Detected Gimp Tag")) { 180 | fakeReason += "Detected Gimp Tag" + "\n"; 181 | } 182 | } 183 | if (string.toUpperCase().contains("COREL")) { 184 | fakeness += 10; 185 | if (!fakeReason.contains("Detected Corel Tag")) { 186 | fakeReason += "Detected Corel Tag" + "\n"; 187 | } 188 | } 189 | if (string.toUpperCase().contains("PAINT")) { 190 | fakeness += 10; 191 | if (!fakeReason.contains("Detected Paint Tag")) { 192 | fakeReason += "Detected Paint Tag" + "\n"; 193 | } 194 | } 195 | if (string.toUpperCase().contains("PIXLR")) { 196 | fakeness += 10; 197 | if (!fakeReason.contains("Detected Pixlr Tag")) { 198 | fakeReason += "Detected Pixlr Tag" + "\n"; 199 | } 200 | } 201 | if (string.contains("Software - Google")) { 202 | fakeness += 10; 203 | if (!fakeReason.contains("Google's Signature Found: Possibly Google+")) { 204 | fakeReason += "Google's Signature Found: Possibly Google+" + "\n"; 205 | } 206 | } 207 | } 208 | 209 | if (ctr < 15) { 210 | fakeness += 4; 211 | fakeReason += "Very Low Metadata Content. Edited" + "\n"; 212 | } else if (ctr < 21) { 213 | fakeness += 3; 214 | fakeReason += "Low Metadata Content. Edited" + "\n"; 215 | } else if (ctr < 30) { 216 | fakeness += 1; 217 | fakeReason += "Average Metadata Content. Edited" + "\n"; 218 | } 219 | int total = fakeness + real; 220 | 221 | float fakenessPercentage = (float) fakeness / total; 222 | float realPercentage = (float) real / total; 223 | ConstantObjects.fakeness = fakenessPercentage; 224 | ConstantObjects.realness = realPercentage; 225 | System.out.println("Fakeness from metedata = " + fakenessPercentage); 226 | 227 | System.err.println("Number of metadata fields = " + ctr); 228 | ObservableList pieChartData 229 | = FXCollections.observableArrayList(); 230 | pie_chart.setData(pieChartData); 231 | pieChartData.add(new PieChart.Data("Fake", fakeness)); 232 | pieChartData.add(new PieChart.Data("Real", real)); 233 | pie_chart.setLegendVisible(false); 234 | pie_chart.setTitle(""); 235 | 236 | final Label caption = new Label(""); 237 | caption.setTextFill(Color.WHITE); 238 | caption.setStyle("-fx-font: 24 arial;"); 239 | final ObservableList children = anchorPane.getChildren(); 240 | children.add(caption); 241 | 242 | PieChart.Data data = pie_chart.getData().get(0); //Fake 243 | data.getNode().addEventHandler(MouseEvent.MOUSE_PRESSED, 244 | new EventHandler() { 245 | @Override 246 | public void handle(MouseEvent e) { 247 | caption.setTranslateX(e.getSceneX()); 248 | caption.setTranslateY(e.getSceneY()); 249 | String text = String.format("%.1f%%", 100 * data.getPieValue() / total); 250 | if (fakeReason.length() > 2) { 251 | JFXSnackbar snackbar = new JFXSnackbar(anchorPane); 252 | snackbar.getStylesheets().add(getClass().getResource("/resources/stylesheets/main.css").toExternalForm()); 253 | snackbar.show(fakeReason, 8000); 254 | } 255 | caption.setText(text); 256 | } 257 | }); 258 | 259 | PieChart.Data data1 = pie_chart.getData().get(1); //Fake 260 | data1.getNode().addEventHandler(MouseEvent.MOUSE_PRESSED, 261 | new EventHandler() { 262 | @Override 263 | public void handle(MouseEvent e) { 264 | caption.setTranslateX(e.getSceneX()); 265 | caption.setTranslateY(e.getSceneY()); 266 | String text = String.format("%.1f%%", 100 * data1.getPieValue() / total); 267 | if (realReason.length() > 10) { 268 | JFXSnackbar snackbar = new JFXSnackbar(anchorPane); 269 | snackbar.getStylesheets().add(getClass().getResource("/resources/stylesheets/main.css").toExternalForm()); 270 | snackbar.show(realReason + " Information", 8000); 271 | } 272 | caption.setText(text); 273 | } 274 | }); 275 | 276 | } 277 | 278 | } 279 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/NetworkcreatorController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXComboBox; 4 | import com.jfoenix.controls.JFXSpinner; 5 | import com.jfoenix.controls.JFXTextField; 6 | import com.gc.fakeimagedetection.core.listener.NeuralNetworkCreationCompleteListener; 7 | import com.gc.fakeimagedetection.core.neuralnet.MLPNetworkMaker; 8 | import com.gc.fakeimagedetection.ui.alert.Calert; 9 | import java.io.File; 10 | import java.net.URL; 11 | import java.util.ArrayList; 12 | import java.util.Arrays; 13 | import java.util.ResourceBundle; 14 | import javafx.collections.FXCollections; 15 | import javafx.collections.ObservableList; 16 | import javafx.event.ActionEvent; 17 | import javafx.fxml.FXML; 18 | import javafx.fxml.Initializable; 19 | import javafx.scene.control.Alert; 20 | import javafx.scene.layout.AnchorPane; 21 | import javafx.scene.layout.Pane; 22 | import javafx.stage.FileChooser; 23 | import org.neuroph.core.NeuralNetwork; 24 | import org.neuroph.imgrec.ColorMode; 25 | import org.neuroph.imgrec.image.Dimension; 26 | import org.neuroph.util.TransferFunctionType; 27 | 28 | public class NetworkcreatorController implements Initializable, NeuralNetworkCreationCompleteListener { 29 | 30 | @FXML 31 | private JFXTextField neuralNetLabel; 32 | @FXML 33 | private JFXTextField width; 34 | @FXML 35 | private JFXTextField height; 36 | @FXML 37 | private JFXComboBox colorMode; 38 | @FXML 39 | private JFXTextField neuronLabelList; 40 | @FXML 41 | private JFXTextField neuronCountList; 42 | @FXML 43 | private JFXComboBox transferFunction; 44 | @FXML 45 | private Pane container; 46 | @FXML 47 | private AnchorPane rootPane; 48 | @FXML 49 | private JFXSpinner loadingSpinner; 50 | 51 | @Override 52 | public void initialize(URL url, ResourceBundle rb) { 53 | loadingSpinner.setVisible(false); 54 | 55 | //Add ColorModes , 56 | ObservableList list = FXCollections.observableArrayList(); 57 | list.add("COLOR_RGB"); 58 | list.add("COLOR_HSL"); 59 | list.add("BLACK_AND_WHITE"); 60 | colorMode.getItems().setAll(list); 61 | 62 | //Add TransferFunctionss 63 | ObservableList listTransferFunctions = FXCollections.observableArrayList(); 64 | listTransferFunctions.add("LINEAR"); 65 | listTransferFunctions.add("RAMP"); 66 | listTransferFunctions.add("STEP"); 67 | listTransferFunctions.add("SIGMOID"); 68 | listTransferFunctions.add("TANH"); 69 | listTransferFunctions.add("GAUSSIAN"); 70 | listTransferFunctions.add("TRAPEZOID"); 71 | listTransferFunctions.add("SGN"); 72 | listTransferFunctions.add("SIN"); 73 | listTransferFunctions.add("LOG"); 74 | transferFunction.getItems().setAll(listTransferFunctions); 75 | 76 | } 77 | 78 | @FXML 79 | private void saveNeuralNet(ActionEvent event) { 80 | String neuralNetLbl = neuralNetLabel.getText(); 81 | Dimension samplingDimension = new Dimension(Integer.parseInt(width.getText()), 82 | Integer.parseInt(height.getText())); 83 | ColorMode mode; 84 | switch (colorMode.getSelectionModel().getSelectedItem()) { 85 | case "COLOR_RGB": 86 | mode = ColorMode.COLOR_RGB; 87 | break; 88 | case "COLOR_HSL": 89 | mode = ColorMode.COLOR_HSL; 90 | break; 91 | case "BLACK_AND_WHITE": 92 | mode = ColorMode.COLOR_RGB; 93 | break; 94 | default: 95 | mode = ColorMode.COLOR_RGB; 96 | break; 97 | } 98 | TransferFunctionType tFunction; 99 | switch (transferFunction.getSelectionModel().getSelectedItem()) { 100 | case "LINEAR": 101 | tFunction = TransferFunctionType.LINEAR; 102 | break; 103 | case "RAMP": 104 | tFunction = TransferFunctionType.RAMP; 105 | break; 106 | case "STEP": 107 | tFunction = TransferFunctionType.STEP; 108 | break; 109 | case "SIGMOID": 110 | tFunction = TransferFunctionType.SIGMOID; 111 | break; 112 | case "TANH": 113 | tFunction = TransferFunctionType.TANH; 114 | break; 115 | case "GAUSSIAN": 116 | tFunction = TransferFunctionType.GAUSSIAN; 117 | break; 118 | case "TRAPEZOID": 119 | tFunction = TransferFunctionType.TRAPEZOID; 120 | break; 121 | case "SGN": 122 | tFunction = TransferFunctionType.SGN; 123 | break; 124 | case "SIN": 125 | tFunction = TransferFunctionType.SIN; 126 | break; 127 | case "LOG": 128 | tFunction = TransferFunctionType.LOG; 129 | break; 130 | default: 131 | tFunction = TransferFunctionType.GAUSSIAN; 132 | break; 133 | } 134 | 135 | ArrayList neuronLabels = new ArrayList(Arrays.asList(neuronLabelList.getText().split("[,]"))); 136 | ArrayList neuronCounts = new ArrayList(); 137 | 138 | for (String neuronCount : neuronCountList.getText().split("[,]")) { 139 | neuronCounts.add(Integer.parseInt(neuronCount.replaceAll(" ", ""))); 140 | System.out.println("neuronCounts = " + neuronCount); 141 | } 142 | 143 | //Show File save dialog 144 | FileChooser fileChooser = new FileChooser(); 145 | fileChooser.setTitle("Save Neural Network"); 146 | File file = fileChooser.showSaveDialog(rootPane.getScene().getWindow()); 147 | if (file == null) { 148 | Calert.showAlert("Not a valid File", "Select target again", Alert.AlertType.ERROR); 149 | return; 150 | } 151 | MLPNetworkMaker maker = new MLPNetworkMaker(neuralNetLbl, samplingDimension, mode, neuronLabels, neuronCounts, tFunction, file.getAbsolutePath()); 152 | maker.setListener(this); 153 | Thread nnetCreator = new Thread(maker); 154 | nnetCreator.start(); 155 | loadingSpinner.setVisible(true); 156 | } 157 | 158 | @Override 159 | public void networkCreationComplete(Boolean flag) { 160 | loadingSpinner.setVisible(false); 161 | if (flag) { 162 | Calert.showAlert("Done", "Neural Network Saved Successfully", Alert.AlertType.INFORMATION); 163 | } 164 | } 165 | 166 | } 167 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/NeuralnetInterfaceController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.jfoenix.controls.JFXSnackbar; 5 | import com.gc.fakeimagedetection.core.constants.ConstantObjects; 6 | import com.gc.fakeimagedetection.core.errorlevelanalysis.FIDErrorLevelAnalysis; 7 | import com.gc.fakeimagedetection.core.listener.ErrorLevelAnalysisListener; 8 | import com.gc.fakeimagedetection.core.listener.NeuralnetProcessorListener; 9 | import com.gc.fakeimagedetection.core.metadata.MetadataProcessor; 10 | import com.gc.fakeimagedetection.core.processor.NeuralNetProcessor; 11 | import com.gc.fakeimagedetection.core.trainer.SingleImageTrainer; 12 | import com.gc.fakeimagedetection.core.listener.ThreadCompleteListener; 13 | import com.gc.fakeimagedetection.ui.alert.Calert; 14 | import ij.ImagePlus; 15 | import java.awt.Dimension; 16 | import java.awt.image.BufferedImage; 17 | import java.io.IOException; 18 | import java.net.URL; 19 | import java.text.DecimalFormat; 20 | import java.util.HashMap; 21 | import java.util.Optional; 22 | import java.util.ResourceBundle; 23 | import java.util.logging.Level; 24 | import java.util.logging.Logger; 25 | import javafx.animation.KeyFrame; 26 | import javafx.animation.KeyValue; 27 | import javafx.animation.ParallelTransition; 28 | import javafx.animation.ScaleTransition; 29 | import javafx.animation.Timeline; 30 | import javafx.animation.TranslateTransition; 31 | import javafx.application.Platform; 32 | import javafx.event.Event; 33 | import javafx.event.EventHandler; 34 | import javafx.fxml.FXML; 35 | import javafx.fxml.FXMLLoader; 36 | import javafx.fxml.Initializable; 37 | import javafx.scene.Scene; 38 | import javafx.scene.control.Alert; 39 | import javafx.scene.control.Alert.AlertType; 40 | import javafx.scene.control.ButtonBar.ButtonData; 41 | import javafx.scene.control.ButtonType; 42 | import javafx.scene.image.ImageView; 43 | import javafx.scene.input.MouseButton; 44 | import javafx.scene.input.MouseEvent; 45 | import javafx.scene.layout.AnchorPane; 46 | import javafx.scene.layout.StackPane; 47 | import javafx.scene.text.Text; 48 | import javafx.stage.Stage; 49 | import javafx.util.Duration; 50 | import javax.imageio.ImageIO; 51 | 52 | public class NeuralnetInterfaceController implements 53 | Initializable, ErrorLevelAnalysisListener, ThreadCompleteListener, NeuralnetProcessorListener { 54 | 55 | public static String imageLocation = ""; 56 | 57 | public static String getImageLocation() { 58 | return imageLocation = LaunchScreeenController.processingFile.getAbsolutePath(); 59 | } 60 | 61 | @FXML 62 | private StackPane rootPane; 63 | @FXML 64 | private ImageView backgroundImageView; 65 | @FXML 66 | private AnchorPane anchorPane; 67 | @FXML 68 | private Text description; 69 | @FXML 70 | private Text christopher; 71 | @FXML 72 | private JFXButton navigation_button; 73 | @FXML 74 | private ImageView homeIcon; 75 | 76 | NeuralnetInterfaceController thisObject = this; 77 | ScaleTransition bulgingTransition; 78 | FIDErrorLevelAnalysis elaAnalyzer; 79 | NeuralNetProcessor nprocessor; 80 | BufferedImage elaImage; 81 | 82 | @Override 83 | public void initialize(URL url, ResourceBundle rb) { 84 | startAnimation(); 85 | getImageLocation(); 86 | 87 | elaAnalyzer = new FIDErrorLevelAnalysis(imageLocation, 95, new Dimension(100, 100), this); 88 | elaAnalyzer.setName("elaAnalyzer"); 89 | elaAnalyzer.start(); 90 | 91 | } 92 | 93 | private void startAnimation() { 94 | navigation_button.setText("Applying ELA on Image"); 95 | float animationExtension = 1.2f; 96 | bulgingTransition = new ScaleTransition(Duration.millis(2000), navigation_button); 97 | bulgingTransition.setToX(animationExtension); 98 | bulgingTransition.setToY(animationExtension); 99 | bulgingTransition.autoReverseProperty().setValue(true); 100 | bulgingTransition.setCycleCount(bulgingTransition.INDEFINITE); 101 | bulgingTransition.play(); 102 | } 103 | 104 | @FXML 105 | private void loadAnimation(MouseEvent event) { 106 | } 107 | 108 | @FXML 109 | private void rollBack(MouseEvent event) { 110 | LaunchScreeenController.processingFile = null; 111 | MetadataProcessor.extracted_data = ""; 112 | try { 113 | Stage stage = (Stage) rootPane.getScene().getWindow(); 114 | Scene pane = new Scene(FXMLLoader.load(getClass().getResource("/resources/fxml/launch.fxml"))); 115 | stage.setScene(pane); 116 | } catch (IOException ex) { 117 | Logger.getLogger(NeuralnetInterfaceController.class.getName()).log(Level.SEVERE, null, ex); 118 | } 119 | } 120 | 121 | void updateIndicatorText(String message) { 122 | Platform.runLater(new Runnable() { 123 | @Override 124 | public void run() { 125 | navigation_button.setText(message); 126 | } 127 | }); 128 | } 129 | 130 | void finalMoveOfIndicator() { 131 | Platform.runLater(new Runnable() { 132 | @Override 133 | public void run() { 134 | Timeline timeline = new Timeline(); 135 | timeline.setCycleCount(1); 136 | 137 | KeyValue keyValueX = new KeyValue(navigation_button.prefWidthProperty(), 300); 138 | KeyFrame keyFrame = new KeyFrame(Duration.millis(2000), keyValueX); 139 | timeline.getKeyFrames().add(keyFrame); 140 | 141 | timeline.play(); 142 | navigation_button.setStyle("-fx-background-radius: 0px;"); 143 | } 144 | }); 145 | } 146 | 147 | void loadResult(HashMap result) { 148 | System.out.println("Metadata Result: Fakeness = " + ConstantObjects.fakeness); 149 | if (ConstantObjects.fakeness < 0) { 150 | System.out.println("Invalid Result from metadata"); 151 | } 152 | 153 | Platform.runLater(new Runnable() { 154 | final float NEURAL_NET_WEIGHT = 0.4f; 155 | final float METADATA_NET_WEIGHT = 1-NEURAL_NET_WEIGHT; 156 | 157 | @Override 158 | public void run() { 159 | double real = result.get("real") * 100; 160 | double fake = result.get("faked") * 100; 161 | 162 | DecimalFormat df2 = new DecimalFormat(".#"); 163 | if (ConstantObjects.shouldPropogateResult) { 164 | real = (real*NEURAL_NET_WEIGHT) + (METADATA_NET_WEIGHT * ConstantObjects.realness*100); 165 | fake = (fake*NEURAL_NET_WEIGHT) + (METADATA_NET_WEIGHT * ConstantObjects.fakeness*100); 166 | } 167 | 168 | if (real < 10 && fake < 10) { 169 | String possibility; 170 | if (real >= fake) { 171 | possibility = "Possibly Real"; 172 | } else { 173 | possibility = "Possibly Fake"; 174 | } 175 | navigation_button.setStyle("-fx-background-color:#EF6C00"); 176 | navigation_button.setText("Cant Determine whether fake or not " + possibility); 177 | 178 | } else if (fake > real) { 179 | navigation_button.setStyle("-fx-background-color:#f44336"); 180 | navigation_button.setText("FAKE IMAGE" + "\nConfidence :" + df2.format(fake) + "%"); 181 | } else if (fake < real) { 182 | navigation_button.setStyle("-fx-background-color:#4CAF50"); 183 | navigation_button.setText("REAL IMAGE" + "\nConfidence :" + df2.format(real) + "%"); 184 | } else { 185 | navigation_button.setStyle("-fx-background-color:#4CAF50"); 186 | navigation_button.setText("Process Failed. 50-50 Chance"); 187 | } 188 | 189 | final JFXSnackbar snackbar = new JFXSnackbar(rootPane); 190 | snackbar.getStylesheets().add(getClass().getResource("/resources/stylesheets/main.css").toExternalForm()); 191 | EventHandler handler = new EventHandler() { 192 | @Override 193 | public void handle(Event event) { 194 | snackbar.unregisterSnackbarContainer(rootPane); 195 | Alert alert = new Alert(AlertType.CONFIRMATION); 196 | alert.setTitle("Confirmation Dialog"); 197 | alert.setContentText("Is this image Fake or Real ?"); 198 | 199 | ButtonType fakeButton = new ButtonType("Fake"); 200 | ButtonType realButton = new ButtonType("Real"); 201 | ButtonType buttonTypeCancel = new ButtonType("Cancel", ButtonData.CANCEL_CLOSE); 202 | 203 | alert.getButtonTypes().setAll(fakeButton, realButton, buttonTypeCancel); 204 | 205 | Optional result = alert.showAndWait(); 206 | if (result.get() == fakeButton) { 207 | navigation_button.setText("Learning..."); 208 | SingleImageTrainer learner 209 | = new SingleImageTrainer(NeuralNetProcessor.nnet, elaImage, false); 210 | learner.addListener(thisObject); 211 | learner.setName("learner"); 212 | learner.start(); 213 | } else if (result.get() == realButton) { 214 | navigation_button.setText("Learning..."); 215 | SingleImageTrainer learner 216 | = new SingleImageTrainer(NeuralNetProcessor.nnet, elaImage, true); 217 | learner.addListener(thisObject); 218 | learner.setName("learner"); 219 | learner.start(); 220 | } else { 221 | 222 | } 223 | } 224 | }; 225 | snackbar.show("Isn't That Right ? Help Me Grow", "Okay", 10000, handler); 226 | 227 | addELAListener(); 228 | } 229 | 230 | private void addELAListener() { 231 | navigation_button.setOnAction((e) -> { 232 | }); 233 | 234 | navigation_button.setOnMousePressed(new EventHandler() { 235 | @Override 236 | public void handle(MouseEvent event) { 237 | if (event.getButton() == MouseButton.PRIMARY) { 238 | new ImagePlus("Error Level Analysis", elaImage).show(); 239 | } else if (event.getButton() == MouseButton.SECONDARY) { 240 | try { 241 | new ImagePlus("Original Image", ImageIO.read(LaunchScreeenController.processingFile)).show(); 242 | } catch (IOException ex) { 243 | Logger.getLogger(NeuralnetInterfaceController.class.getName()).log(Level.SEVERE, null, ex); 244 | } 245 | } 246 | } 247 | }); 248 | } 249 | }); 250 | } 251 | 252 | private void removeBannersandDescs() { 253 | TranslateTransition tChristopher = new TranslateTransition(Duration.millis(1000), christopher); 254 | TranslateTransition tDescription = new TranslateTransition(Duration.millis(1000), description); 255 | tChristopher.setToY(-500); 256 | tDescription.setToY(-500); 257 | ParallelTransition pt = new ParallelTransition(tChristopher, tDescription); 258 | pt.play(); 259 | 260 | } 261 | 262 | @Override 263 | public void notifyOfThreadComplete(Thread thread) { 264 | switch (thread.getName()) { 265 | case "learner": 266 | updateIndicatorText("Learning Complete"); 267 | break; 268 | } 269 | } 270 | 271 | @Override 272 | public void elaCompleted(BufferedImage image) { 273 | updateIndicatorText("Serializing Image"); 274 | elaImage = image; 275 | updateIndicatorText("Connecting to Neural Network"); 276 | nprocessor = new NeuralNetProcessor(elaImage); 277 | nprocessor.setName("nprocessor"); 278 | nprocessor.addListener(this); 279 | nprocessor.setListener(this); 280 | nprocessor.start(); 281 | removeBannersandDescs(); 282 | } 283 | 284 | @Override 285 | public void neuralnetProcessCompleted(HashMap result) { 286 | if (result == null) { 287 | Platform.runLater(new Runnable() { 288 | @Override 289 | public void run() { 290 | Calert.showAlert("Forced Rollback", "Image Detection Failed:\nCorrupted File", AlertType.ERROR); 291 | rollBack(null); 292 | return; 293 | } 294 | }); 295 | } 296 | bulgingTransition.stop(); 297 | updateIndicatorText("Done"); 298 | System.out.println("Neural net result:-\n" + result); 299 | loadResult(result); 300 | } 301 | } 302 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/SingleImageAnalyzerController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.jfoenix.controls.JFXCheckBox; 5 | import com.gc.fakeimagedetection.ui.alert.Calert; 6 | import static com.gc.fakeimagedetection.core.processor.NeuralNetProcessor.nnet; 7 | import java.io.File; 8 | import java.io.FileInputStream; 9 | import java.io.FileNotFoundException; 10 | import java.io.IOException; 11 | import java.net.URL; 12 | import java.util.HashMap; 13 | import java.util.ResourceBundle; 14 | import java.util.logging.Level; 15 | import java.util.logging.Logger; 16 | import javafx.event.ActionEvent; 17 | import javafx.fxml.FXML; 18 | import javafx.fxml.Initializable; 19 | import javafx.scene.control.Alert; 20 | import javafx.scene.layout.AnchorPane; 21 | import javafx.stage.FileChooser; 22 | import javax.imageio.ImageIO; 23 | import org.neuroph.core.NeuralNetwork; 24 | import org.neuroph.imgrec.ImageRecognitionPlugin; 25 | 26 | public class SingleImageAnalyzerController implements Initializable { 27 | 28 | @FXML 29 | private JFXButton neuralSource; 30 | @FXML 31 | private JFXCheckBox nnIndicator; 32 | @FXML 33 | private JFXButton imgSource; 34 | @FXML 35 | private JFXCheckBox imgIndicator; 36 | @FXML 37 | private JFXButton startButton; 38 | 39 | File nnetSrc; 40 | File imgSrc; 41 | @FXML 42 | private AnchorPane rootPane; 43 | 44 | @Override 45 | public void initialize(URL url, ResourceBundle rb) { 46 | // TODO 47 | } 48 | 49 | @FXML 50 | private void loadNeuralNetwork(ActionEvent event) { 51 | FileChooser fileChooser = new FileChooser(); 52 | fileChooser.setTitle("Select Neural Network"); 53 | nnetSrc = fileChooser.showOpenDialog(rootPane.getScene().getWindow()); 54 | if (nnetSrc != null) { 55 | nnIndicator.setSelected(true); 56 | } 57 | } 58 | 59 | @FXML 60 | private void loadImage(ActionEvent event) { 61 | FileChooser fileChooser = new FileChooser(); 62 | fileChooser.setTitle("Select Image"); 63 | imgSrc = fileChooser.showOpenDialog(rootPane.getScene().getWindow()); 64 | if (imgSrc != null) { 65 | imgIndicator.setSelected(true); 66 | } 67 | } 68 | 69 | @FXML 70 | private void startCheck(ActionEvent event) throws IOException { 71 | if (nnetSrc == null || imgSrc == null) { 72 | Calert.showAlert("Invalid Data", "Select Required Files", Alert.AlertType.ERROR); 73 | return; 74 | } 75 | try { 76 | nnet = NeuralNetwork.load(new FileInputStream(nnetSrc)); // load trained neural network saved with Neuroph Studio 77 | System.out.println("Learning Rule = " + nnet.getLearningRule()); 78 | ImageRecognitionPlugin imageRecognition = (ImageRecognitionPlugin) nnet.getPlugin(ImageRecognitionPlugin.class); // get the 79 | HashMap output = imageRecognition.recognizeImage(ImageIO.read(imgSrc)); 80 | if (output == null) { 81 | System.err.println("Image Recognition Failed"); 82 | } 83 | double real = output.get("real"); 84 | double fake = output.get("faked"); 85 | System.out.println(output.toString()); 86 | Calert.showAlert("Result", "Real = " + real + "\nFake = " + fake, Alert.AlertType.INFORMATION); 87 | } catch (FileNotFoundException ex) { 88 | Logger.getLogger(SingleImageAnalyzerController.class.getName()).log(Level.SEVERE, null, ex); 89 | } 90 | } 91 | 92 | } 93 | -------------------------------------------------------------------------------- /src/com/gc/fakeimagedetection/ui/controllers/TrainingInterfaceController.java: -------------------------------------------------------------------------------- 1 | package com.gc.fakeimagedetection.ui.controllers; 2 | 3 | import com.jfoenix.controls.JFXButton; 4 | import com.jfoenix.controls.JFXCheckBox; 5 | import com.jfoenix.controls.JFXSpinner; 6 | import com.jfoenix.controls.JFXTextField; 7 | import com.gc.fakeimagedetection.core.listener.BatchImageTrainingListener; 8 | import com.gc.fakeimagedetection.ui.alert.Calert; 9 | import com.gc.fakeimagedetection.core.trainer.BatchImageTrainer; 10 | import java.awt.Dimension; 11 | import java.io.File; 12 | import java.net.URL; 13 | import java.util.ArrayList; 14 | import java.util.ResourceBundle; 15 | import javafx.application.Platform; 16 | import javafx.beans.value.ChangeListener; 17 | import javafx.beans.value.ObservableValue; 18 | import javafx.event.ActionEvent; 19 | import javafx.fxml.FXML; 20 | import javafx.fxml.FXMLLoader; 21 | import javafx.fxml.Initializable; 22 | import javafx.scene.Parent; 23 | import javafx.scene.Scene; 24 | import javafx.scene.chart.CategoryAxis; 25 | import javafx.scene.chart.LineChart; 26 | import javafx.scene.chart.NumberAxis; 27 | import javafx.scene.chart.XYChart; 28 | import javafx.scene.control.Alert; 29 | import javafx.scene.control.CheckBox; 30 | import javafx.scene.layout.AnchorPane; 31 | import javafx.scene.layout.Pane; 32 | import javafx.stage.DirectoryChooser; 33 | import javafx.stage.FileChooser; 34 | import javafx.stage.Modality; 35 | import javafx.stage.Stage; 36 | 37 | public class TrainingInterfaceController implements 38 | Initializable, BatchImageTrainingListener { 39 | 40 | @FXML 41 | private JFXButton sourceIndicator; 42 | @FXML 43 | private CheckBox srcIndicator; 44 | @FXML 45 | private JFXTextField realLabel; 46 | @FXML 47 | private JFXTextField fakeLabel; 48 | @FXML 49 | private JFXButton startButton; 50 | @FXML 51 | private AnchorPane rootPane; 52 | @FXML 53 | private JFXTextField width; 54 | @FXML 55 | private JFXTextField height; 56 | @FXML 57 | private JFXTextField learningRate; 58 | @FXML 59 | private JFXTextField momentum; 60 | @FXML 61 | private JFXTextField maxError; 62 | @FXML 63 | private LineChart errorChart; 64 | @FXML 65 | private NumberAxis yAxis; 66 | @FXML 67 | private CategoryAxis xAxis; 68 | @FXML 69 | private JFXButton saveButton; 70 | @FXML 71 | private JFXButton neuralSource; 72 | @FXML 73 | private JFXCheckBox nnIndicator; 74 | @FXML 75 | private Pane containerPlane; 76 | @FXML 77 | private JFXSpinner spinner; 78 | 79 | 80 | ArrayList imageLabels; 81 | File srcDir = null; 82 | File nnFile = null; 83 | String rLabel = ""; 84 | String fLabel = ""; 85 | XYChart.Series series; 86 | BatchImageTrainer neuralTrainer; 87 | 88 | @Override 89 | public void initialize(URL url, ResourceBundle rb) { 90 | imageLabels = new ArrayList<>(); 91 | series = new XYChart.Series(); 92 | series.setName("Learning Curve 1"); 93 | errorChart.getData().add(series); 94 | 95 | spinner.setVisible(false); 96 | } 97 | 98 | 99 | @FXML 100 | private void loadImageSource(ActionEvent event) { 101 | DirectoryChooser chooser = new DirectoryChooser(); 102 | chooser.setTitle("Choose Traing Set"); 103 | srcDir = chooser.showDialog(rootPane.getScene().getWindow()); 104 | if (srcDir == null) { 105 | Calert.showAlert("Error", "Not a valid folder", Alert.AlertType.ERROR); 106 | return; 107 | } 108 | 109 | System.out.println("Loading Dataset from " + srcDir.getAbsolutePath()); 110 | srcIndicator.setSelected(true); 111 | } 112 | 113 | @FXML 114 | private void startTraining(ActionEvent event) { 115 | switch (startButton.getAccessibleText()) { 116 | case "start": 117 | try { 118 | rLabel = realLabel.getText(); 119 | fLabel = fakeLabel.getText(); 120 | imageLabels.add(fLabel); 121 | imageLabels.add(rLabel); 122 | int sampledWidth = Integer.parseInt(width.getText()); 123 | int sampledheight = Integer.parseInt(height.getText()); 124 | float lRate = Float.parseFloat(learningRate.getText()); 125 | float moment = Float.parseFloat(momentum.getText()); 126 | float mError = Float.parseFloat(maxError.getText()); 127 | if (srcDir == null || nnFile == null) { 128 | Calert.showAlert("Incomplete Configuration Data", "Check parameters", Alert.AlertType.ERROR); 129 | return; 130 | } 131 | 132 | System.out.println("Starting training procedure"); 133 | neuralTrainer = new BatchImageTrainer(srcDir, nnFile, 134 | new Dimension(sampledWidth, sampledWidth), imageLabels, this); 135 | neuralTrainer.setMaxError(mError); 136 | neuralTrainer.setMomentum(moment); 137 | neuralTrainer.setLearningRate(lRate); 138 | neuralTrainer.start(); 139 | spinner.setVisible(true); 140 | 141 | startButton.setAccessibleText("stop"); 142 | startButton.setStyle("-fx-background-color:#e53935;-fx-text-fill:#ffffff"); 143 | startButton.setText("Stop Training"); 144 | } catch (Exception e) { 145 | Calert.showAlert("Incomplete Configuration Data", e.getMessage(), Alert.AlertType.ERROR); 146 | } 147 | break; 148 | case "stop": 149 | neuralTrainer.stopLearning(); 150 | startButton.setAccessibleText("stopped"); 151 | startButton.setText("Stopped"); 152 | break; 153 | default: 154 | System.out.println("Invalid Accessible Text"); 155 | 156 | } 157 | 158 | } 159 | 160 | @FXML 161 | private void saveLearnedNetwork(ActionEvent event) { 162 | FileChooser fileChooser = new FileChooser(); 163 | fileChooser.setTitle("Save Neural Network"); 164 | File file = fileChooser.showSaveDialog(rootPane.getScene().getWindow()); 165 | neuralTrainer.saveLearnedNetwork(file.getAbsolutePath()); 166 | } 167 | 168 | @FXML 169 | private void loadNeuralNetwork(ActionEvent event) { 170 | FileChooser fileChooser = new FileChooser(); 171 | fileChooser.setTitle("Open Resource File"); 172 | 173 | fileChooser.setSelectedExtensionFilter(new FileChooser.ExtensionFilter("Neural Nets", "*.nnet")); 174 | nnFile = fileChooser.showOpenDialog(rootPane.getScene().getWindow()); 175 | 176 | if (nnFile == null) { 177 | Calert.showAlert("Error", "Not a valid neural network", Alert.AlertType.ERROR); 178 | return; 179 | } 180 | 181 | System.out.println("Training Neural " + nnFile.getAbsolutePath()); 182 | nnIndicator.setSelected(true); 183 | } 184 | 185 | @FXML 186 | private void loadNewTrainingWindow(ActionEvent event) { 187 | try { 188 | FXMLLoader fxmlLoader = new FXMLLoader(getClass().getResource("/resources/fxml/traininginterface.fxml")); 189 | Parent root1 = (Parent) fxmlLoader.load(); 190 | Stage stage = new Stage(); 191 | stage.initModality(Modality.APPLICATION_MODAL); 192 | stage.setTitle("Neural Network Trainer"); 193 | stage.setScene(new Scene(root1)); 194 | stage.show(); 195 | } catch (Exception e) { 196 | Calert.showAlert("Cant launch new window", e.getMessage(), Alert.AlertType.ERROR); 197 | } 198 | } 199 | 200 | @Override 201 | public void batchImageTrainingCompleted() { 202 | saveButton.setDisable(false); 203 | spinner.setVisible(false); 204 | } 205 | 206 | @Override 207 | public void batchImageTrainingUpdate(int iteration, Double error) { 208 | Platform.runLater(new Runnable() { 209 | @Override 210 | public void run() { 211 | series.getData().add(new XYChart.Data(String.valueOf(iteration), error)); 212 | } 213 | }); 214 | } 215 | 216 | } 217 | -------------------------------------------------------------------------------- /src/resources/fxml/batchimageprocessor.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | -------------------------------------------------------------------------------- /src/resources/fxml/batchimagetester.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | -------------------------------------------------------------------------------- /src/resources/fxml/home.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/src/resources/fxml/home.png -------------------------------------------------------------------------------- /src/resources/fxml/infinity.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/src/resources/fxml/infinity.png -------------------------------------------------------------------------------- /src/resources/fxml/launch.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 |
25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | 71 | 72 | 73 | 74 | 75 | 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | 85 | 86 | 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | 96 | 97 | 98 | 99 | 100 | 101 | 102 |
103 | 104 | -------------------------------------------------------------------------------- /src/resources/fxml/metadatadisplay.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | -------------------------------------------------------------------------------- /src/resources/fxml/metadataresult.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | -------------------------------------------------------------------------------- /src/resources/fxml/networkcreator.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | -------------------------------------------------------------------------------- /src/resources/fxml/neuralinterface.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | 70 | -------------------------------------------------------------------------------- /src/resources/fxml/singleimage.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | -------------------------------------------------------------------------------- /src/resources/fxml/traininginterface.fxml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | -------------------------------------------------------------------------------- /src/resources/icon/icon.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/src/resources/icon/icon.png -------------------------------------------------------------------------------- /src/resources/icon/icon_high.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/afsalashyana/FakeImageDetection/7466fa9f3b01a5e34987651a51aab9172a118bf6/src/resources/icon/icon_high.png -------------------------------------------------------------------------------- /src/resources/stylesheets/main.css: -------------------------------------------------------------------------------- 1 | .panel2{ 2 | -fx-background-color: #0f0f0f; 3 | } 4 | 5 | /*welcome screen main navigation button*/ 6 | .load_image_button{ 7 | -fx-background-color: #03A9F4; 8 | -fx-background-radius: 200px; 9 | -fx-text-fill: #ffffff; 10 | } 11 | 12 | .meta_data_result{ 13 | -fx-background-color: #03A9F4; 14 | -fx-text-fill: #ffffff; 15 | } 16 | 17 | .launch_panel{ 18 | -fx-background-color: black; 19 | } 20 | 21 | /*Overriding default Pie chart colours*/ 22 | .default-color0.chart-pie { -fx-pie-color: #f44336; } 23 | .default-color1.chart-pie { -fx-pie-color: #76FF03; } 24 | 25 | /*Piechart title style*/ 26 | .chart-title { 27 | -fx-text-fill: #ffffff; 28 | -fx-font-size: 1.6em; 29 | } 30 | /*Piechart content styles*/ 31 | .chart-content { 32 | -fx-padding: 30px; 33 | -fx-text-fill: #ffffff; 34 | } 35 | /*Piechart axis label*/ 36 | .axis-label { 37 | -fx-text-fill: #ffffff; 38 | } 39 | 40 | .chart-pie-label-line { 41 | -fx-stroke: #ffffff; 42 | -fx-fill: #ffffff; 43 | } 44 | 45 | .chart-pie-label { 46 | -fx-fill: #ffffff; 47 | -fx-font-size: 1.5em; 48 | } 49 | 50 | /*Metadata result snackbar styling*/ 51 | 52 | .jfx-snackbar-content { 53 | -fx-background-color: #FFFFFF; 54 | } 55 | .jfx-snackbar-toast { 56 | -fx-text-fill: #000000; 57 | -fx-font-size: 16; 58 | } 59 | --------------------------------------------------------------------------------